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A collection of works that investigate social agents, simulations and their real-world impact in text, embodied, and robotics contexts.

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🗣️👥 Awesome Social Agents

Awesome   PRs Welcome   arXiv

For the best experience, we recommend reading this document on the website.

The rise of Large Language Models (LLMs)/foundational models presents new opportunities for simulating complex human social behaviors. As a result, there is a rapidly growing body of work emerging in this domain. We hope to categorize and synergize recent efforts to provide a comprehensive guidebook of social agents weaving together multiple domains, including language, embodiment, and robotics.

Our goal is to offer insights crucial for understanding and harnessing social agents' potential impact on society. We strive to keep these updated regularly and continuously. We greatly appreciate any contributions via PRs, issues, emails, or other methods.

Note

  • Agent and Environment (Sutton and Barto 2018): An agent is a goal-driven decision-maker that sense and act upon the state of the environment. An environment comprises the state outside the agent, including the other agents if any.
  • Social Agent: An agent that interacts with a multi-agent environment.
  • Socially Intelligent Agent: A social agent that interacts and communicates with other agents in a human-interpretable way.
more notes
  1. The social intelligence that we are focusing on is human-like, excluding the collective intelligence in a lot of social animals like ants, bees, fishes.
  2. To understand whether an entity is a (social) agent, we have to situate it in an environment. It is not possible to discuss an agent outside of an environment.
  3. We acknowledge there are many types of definitions for social agents. Our defitions here help narrow down the scope of our survey.

🗂️ Check out the examples of social agents. 📚 Check out the table format of the collected papers here.

📝 We are currently working on a survey paper related to content of this repository. Stay tuned for updates!

Table of Contents

Papers

Surveys and Overview

[6, 2023] Socially intelligent machines that learn from humans and help humans learn, Gweon et al., arXiv

[4, 2024] Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions, Leena Mathur et al., arXiv preprint arXiv:2404.11023

[2, 2024] Social Intelligence Data Infrastructure: Structuring the Present and Navigating the Future, Minzhi Li et al., arXiv preprint arXiv:2403.14659

[4, 2024] Social Skill Training with Large Language Models, Diyi Yang et al., arXiv preprint arXiv:2404.04204

Environments

Text and Speech Environments

[4, 2024] To Tell The Truth: Language of Deception and Language Models, Bodhisattwa Prasad Majumder et al., arXiv preprint arXiv:2311.07092

[3, 2024] Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference, Wei-Lin Chiang et al., arXiv preprint arXiv:2403.04132

[8, 2023] {CALYPSO}: {LLMs} as Dungeon Masters' Assistants, Andrew Zhu et al., The 19th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2023)

[7, 2023] {I} Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons, Zhou et al., Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

[7, 2023] {FIREBALL}: A Dataset of Dungeons and Dragons Actual-Play with Structured Game State Information, Zhu et al., Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

[3, 2023] Fast Multi-Agent Gridworld Environments for Gymnasium, Ini Oguntola et al., GitHub

[03, 2023] Reflexion: Language Agents with Verbal Reinforcement Learning, Noah Shinn et al., arXiv

[12, 2022] Dungeons and Dragons as a Dialog Challenge for Artificial Intelligence, Callison-Burch et al., Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

[11, 2022] Human-level play in the game of Diplomacy by combining language models with strategic reasoning, Meta Fundamental AI Research Diplomacy Team (FAIR)† et al., Science

[11, 2022] Introducing ChatGPT, OpenAI et al., n/a

[8, 2022] Blenderbot 3: a deployed conversational agent that continually learns to responsibly engage, Kurt Shuster et al., arXiv preprint arXiv:2208.03188

[5, 2022] Opt: Open pre-trained transformer language models, Susan Zhang et al., arXiv preprint arXiv:2205.01068

[3, 2022] Report from the nsf future directions workshop on automatic evaluation of dialog: Research directions and challenges, Shikib Mehri et al., arXiv preprint arXiv:2203.10012

[1, 2022] Socio-conversational systems: Three challenges at the crossroads of fields, Chlo{'e} Clavel et al., Frontiers in Robotics and AI

[1, 2022] The Handbook on Socially Interactive Agents: 20 Years of Research on Embodied Conversational Agents, Intelligent Virtual Agents, and Social Robotics Volume 2: Interactivity, Platforms, Application, Birgit Lugrin et al., ACM

[1, 2022] Human evaluation of conversations is an open problem: comparing the sensitivity of various methods for evaluating dialogue agents, Eric Michael Smith et al., arXiv preprint arXiv:2201.04723

[7, 2020] It Takes Two to Lie: One to Lie, and One to Listen, Peskov et al., Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

[3, 2020] The Hanabi challenge: A new frontier for AI research, Nolan Bard et al., Artificial Intelligence

[3, 2020] The Design and Implementation of {X}iao{I}ce, an Empathetic Social Chatbot, Zhou et al., Computational Linguistics

[08, 2019] {OpenSpiel}: A Framework for Reinforcement Learning in Games, Marc Lanctot et al., CoRR

[7, 2019] Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good, Wang et al., Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

[7, 2019] RLCard: A Toolkit for Reinforcement Learning in Card Games, Daochen Zha et al., arXiv preprint arXiv:1910.04376

[4, 2019] Wizard of Wikipedia: Knowledge-Powered Conversational Agents, Emily Dinan et al., International Conference on Learning Representations

[11, 2018] Towards empathetic open-domain conversation models: A new benchmark and dataset, Hannah Rashkin et al., arXiv preprint arXiv:1811.00207

[10, 2018] Decoupling Strategy and Generation in Negotiation Dialogues, He et al., Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

[4, 2018] A knowledge-grounded neural conversation model, Marjan Ghazvininejad et al., Proceedings of the AAAI Conference on Artificial Intelligence

[3, 2018] Towards empathetic human-robot interactions, Pascale Fung et al., Computational Linguistics and Intelligent Text Processing: 17th International Conference, CICLing 2016, Konya, Turkey, April 3--9, 2016, Revised Selected Papers, Part II 17

[9, 2017] Deal or No Deal? End-to-End Learning of Negotiation Dialogues, Lewis et al., Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

[8, 2016] A persona-based neural conversation model, Jiwei Li et al., arXiv preprint arXiv:1603.06155

[11, 2009] The anatomy of ALICE, Richard S Wallace et al., n/a

[1, 2006] Empathic computing, Yang Cai et al., Ambient intelligence in everyday life: Foreword by Emile Aarts

[1, 1966] ELIZA—a computer program for the study of natural language communication between man and machine, Joseph Weizenbaum et al., Commun. ACM

Embodied Environments

[October, 2023] Habitat 3.0: A Co-Habitat for Humans, Avatars and Robots, Puig et al., ICLR

[September, 2020] SEAN: Social Environment for Autonomous Navigation, Tsoi et al., HAI

Virtual Environments

[1, 2024] Visualwebarena: Evaluating multimodal agents on realistic visual web tasks, Jing Yu Koh et al., arXiv preprint arXiv:2401.13649

[1, 2024] Mind2web: Towards a generalist agent for the web, Xiang Deng et al., Advances in Neural Information Processing Systems

[12, 2023] Appagent: Multimodal agents as smartphone users, Zhao Yang et al., arXiv preprint arXiv:2312.13771

[11, 2023] Simulating Iterative Human-AI Interaction in Programming with LLMs, Hussein Mozannar et al., NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following

[7, 2023] Webarena: A realistic web environment for building autonomous agents, Shuyan Zhou et al., arXiv preprint arXiv:2307.13854

[7, 2023] Android in the wild: A large-scale dataset for android device control, Christopher Rawles et al., arXiv preprint arXiv:2307.10088

[3, 2023] The Programmer's Assistant: Conversational Interaction with a Large Language Model for Software Development, Steven I Ross et al., Proceedings of the 28th International Conference on Intelligent User Interfaces

[12, 2022] Webshop: Towards scalable real-world web interaction with grounded language agents, Shunyu Yao et al., Advances in Neural Information Processing Systems

[8, 2022] Minedojo: Building open-ended embodied agents with internet-scale knowledge, Linxi Fan et al., Advances in Neural Information Processing Systems

[7, 2022] A data-driven approach for learning to control computers, Peter C Humphreys et al., International Conference on Machine Learning

[2, 2022] A dataset for interactive vision-language navigation with unknown command feasibility, Andrea Burns et al., European Conference on Computer Vision

[2, 2022] Scienceworld: Is your agent smarter than a 5th grader?, Ruoyao Wang et al., arXiv preprint arXiv:2203.07540

[5, 2021] Androidenv: A reinforcement learning platform for android, Daniel Toyama et al., arXiv preprint arXiv:2105.13231

[3, 2021] Grounding open-domain instructions to automate web support tasks, Nancy Xu et al., arXiv preprint arXiv:2103.16057

[9, 2020] Interactive task learning from GUI-grounded natural language instructions and demonstrations, Toby Jia-Jun Li et al., Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

[5, 2020] Mapping natural language instructions to mobile UI action sequences, Yang Li et al., arXiv preprint arXiv:2005.03776

[4, 2020] The nethack learning environment, Heinrich K{"u}ttler et al., Advances in Neural Information Processing Systems

[3, 2019] Pumice: A multi-modal agent that learns concepts and conditionals from natural language and demonstrations, Toby Jia-Jun Li et al., Proceedings of the 32nd annual ACM symposium on user interface software and technology

[1, 2019] Textworld: A learning environment for text-based games, Marc-Alexandre C{^o}t{'e} et al., Computer Games: 7th Workshop, CGW 2018, Held in Conjunction with the 27th International Conference on Artificial Intelligence, IJCAI 2018, Stockholm, Sweden, July 13, 2018, Revised Selected Papers 7

[6, 2018] Virtualhome: Simulating household activities via programs, Xavier Puig et al., Proceedings of the IEEE conference on computer vision and pattern recognition

[3, 2018] Appinite: A multi-modal interface for specifying data descriptions in programming by demonstration using natural language instructions, Toby Jia-Jun Li et al., 2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

[2, 2018] Reinforcement learning on web interfaces using workflow-guided exploration, Evan Zheran Liu et al., arXiv preprint arXiv:1802.08802

[8, 2017] World of bits: An open-domain platform for web-based agents, Tianlin Shi et al., International Conference on Machine Learning

[5, 2017] Ai2-thor: An interactive 3d environment for visual ai, Eric Kolve et al., arXiv preprint arXiv:1712.05474

[8, 2009] Reinforcement learning for mapping instructions to actions, Satchuthananthavale RK Branavan et al., Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

[7, 2007] Plow: A collaborative task learning agent, James Allen et al., AAAI

Robotics

[03, 2024] Vid2Robot: End-to-end Video-conditioned Policy Learning with Cross-Attention Transformers, Vidhi Jain et al., arXiv

[03, 2024] BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation, Chengshu Li et al., arXiv

[03, 2024] DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset, Alexander Khazatsky et al., arXiv

[03, 2024] Yell At Your Robot: Improving On-the-Fly from Language Corrections, Lucy Xiaoyang Shi et al., arXiv

[3, 2024] RABBIT: A Robot-Assisted Bed Bathing System with Multimodal Perception and Integrated Compliance, Rishabh Madan et al., Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction

[12, 2023] Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis, Yafei Hu et al., arXiv preprint: arXiv:2312.08782

[12, 2023] RoboTube: Learning Household Manipulation from Human Videos with Simulated Twin Environments, Haoyu Xiong et al., Proceedings of The 6th Conference on Robot Learning

[11, 2023] Toward Grounded Commonsense Reasoning, Minae Kwon et al., arXiv preprint arXiv:2306.08651

[10, 2023] Open {X-E}mbodiment: Robotic Learning Datasets and {RT-X} Models, Open X-Embodiment Collaboration et al., arXiv

[9, 2023] How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies, Montserrat Gonzalez Arenas et al., 2nd Workshop on Language and Robot Learning: Language as Grounding

[08, 2023] Co-GAIL: Learning Diverse Strategies for Human-Robot Collaboration, Chen Wang et al., arXiv

[7, 2023] MUTEX: Learning Unified Policies from Multimodal Task Specifications, Rutav Shah et al., 7th Annual Conference on Robot Learning

[7, 2023] Robotic vision for human-robot interaction and collaboration: A survey and systematic review, Nicole Robinson et al., ACM Transactions on Human-Robot Interaction

[6, 2023] Gesture-Informed Robot Assistance via Foundation Models, Li-Heng Lin et al., 7th Annual Conference on Robot Learning

[6, 2023] HomeRobot: Open-Vocabulary Mobile Manipulation, Sriram Yenamandra et al., 7th Annual Conference on Robot Learning

[6, 2023] One Policy to Dress Them All: Learning to Dress People with Diverse Poses and Garments, Yufei Wang et al., Robotics: Science and Systems (RSS)

[4, 2023] 15 Years of (Who)man Robot Interaction: Reviewing the H in Human-Robot Interaction, Katie Winkle et al., J. Hum.-Robot Interact.

[3, 2023] Nonverbal Cues in Human Robot Interaction: A Communication Studies Perspective, Jacqueline Urakami et al., J. Hum.-Robot Interact.

[01, 2023] Benchmarks and Algorithms for Offline Preference-Based Reward Learning, Daniel Shin et al., arXiv

[12, 2022] See, Hear, and Feel: Smart Sensory Fusion for Robotic Manipulation, Hao Li et al., CoRL

[12, 2022] Transformers Are Adaptable Task Planners, Vidhi Jain et al., 6th Annual Conference on Robot Learning

[10, 2022] A survey of multi-agent Human--Robot Interaction systems, Abhinav Dahiya et al., Robotics and Autonomous Systems

[10, 2022] Rcare world: A human-centric simulation world for caregiving robots, Ruolin Ye et al., 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

[8, 2022] Do As I Can and Not As I Say: Grounding Language in Robotic Affordances, Michael Ahn et al., arXiv preprint arXiv:2204.01691

[6, 2022] Inner Monologue: Embodied Reasoning through Planning with Language Models, Wenlong Huang et al., arXiv preprint arXiv:2207.05608

[6, 2021] A taxonomy to structure and analyze human--robot interaction, Linda Onnasch et al., International Journal of Social Robotics

[3, 2020] Threedworld: A platform for interactive multi-modal physical simulation, Chuang Gan et al., arXiv preprint arXiv:2007.04954

[10, 2019] Vision-and-Dialog Navigation, Jesse Thomason et al., Conference on Robot Learning (CoRL)

[7, 2018] Towards a robust interactive and learning social robot, Michiel De Jong et al., Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems

[4, 2016] Human--robot interaction: status and challenges, Thomas B Sheridan et al., Human factors

Modeling

In-context Learning

[May, 2023] Voyager: An Open-Ended Embodied Agent with Large Language Models, Guanzhi Wang et al., arXiv

[March, 2023] Language Models can Solve Computer Tasks, Geunwoo Kim et al., arXiv

[September, 2024] LASER: LLM Agent with State-Space Exploration for Web Navigation, Kaixin Ma et al., arXiv

[May, 2023] Hierarchical Prompting Assists Large Language Model on Web Navigation, Abishek Sridhar et al., arXiv

[January, 2024] Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Control, Longtao Zheng et al., The Twelfth International Conference on Learning Representations

[November, 2023] AdaPlanner: Adaptive Planning from Feedback with Language Models, Haotian Sun et al., Thirty-seventh Conference on Neural Information Processing Systems

[May, 2023] SPRING: Studying the Paper and Reasoning to Play Games, Yue Wu et al., arXiv

[March, 2023] DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents, Varun Nair et al., arXiv

Finetuning

[October, 2023] Understanding HTML with Large Language Models, Izzeddin Gur et al., arXiv
[ May, 2023] Instruction-Finetuned Foundation Models for Multimodal Web Navigation, Hiroki Furuta et al., ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation Models

[October, 2023] ReAct: Synergizing Reasoning and Acting in Language Models, Shunyu Yao et al., arXiv

[January, 2024] A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis, Izzeddin Gur et al., The Twelfth International Conference on Learning Representations

[November, 2023] From Pixels to {UI} Actions: Learning to Follow Instructions via Graphical User Interfaces, Peter Shaw et al., Thirty-seventh Conference on Neural Information Processing Systems

[January, 2024] GPT-4V(ision) is a Generalist Web Agent, if Grounded, Boyuan Zheng et al., arXiv

[February, 2024] Dual-View Visual Contextualization for Web Navigation, Jihyung Kil et al., arXiv

Reinforcement learning

Evaluating social agents

Evaluating text social agents

[October, 2024] SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents, Xuhui Zhou et al., ICLR

[October, 2023] CompeteAI: Understanding the Competition Behaviors in Large Language Model-based Agents, Qinlin Zhao et al., arXiv

[March, 2024] RoleInteract: Evaluating the Social Interaction of Role-Playing Agents, Hongzhan Chen et al., arXiv

[September, 2023] Approximating Online Human Evaluation of Social Chatbots with Prompting, Svikhnushina et al., Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue

[December, 2023] CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society, Guohao Li et al., Advances in Neural Information Processing Systems

[October, 2023] Llm-based agent society investigation: Collaboration and confrontation in avalon gameplay, Yihuai Lan et al., arXiv preprint arXiv:2310.14985

[August, 2023] CharacterChat: Learning towards Conversational AI with Personalized Social Support, Quan Tu et al., arXiv

[October, 2023] AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems, Junjie Zhang et al., arXiv

[March, 2024] How Far Are We on the Decision-Making of LLMs? Evaluating LLMs' Gaming Ability in Multi-Agent Environments, Jen-tse Huang et al., arXiv

[August, 2023] ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate, Chi-Min Chan et al., arXiv

[February, 2024] Automatic Evaluation for Mental Health Counseling using LLMs, Anqi Li et al., arXiv

[February, 2024] How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis, Federico Bianchi et al., arXiv

[May, 2023] PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits, Hang Jiang et al., NAACL Findings

[February, 2024] Can Large Language Model Agents Simulate Human Trust Behaviors?, Chengxing Xie et al., ArXiv

[January, 2024] LLM Harmony: Multi-Agent Communication for Problem Solving, Sumedh Rasal et al., ArXiv

[November, 2021] A Comprehensive Assessment of Dialog Evaluation Metrics, Yeh et al., The First Workshop on Evaluations and Assessments of Neural Conversation Systems

[July, 2020] {C}onvo{K}it: A Toolkit for the Analysis of Conversations, Chang et al., Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue

[May, 2023] Psychological Metrics for Dialog System Evaluation, Salvatore Giorgi et al., arXiv

[May, 2023] ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systems, Sarik Ghazarian et al., arXiv

[November, 2020] {GRADE}: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems, Huang et al., Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

[July, 2020] Unsupervised Evaluation of Interactive Dialog with {D}ialo{GPT}, Mehri et al., Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue

[December, 2023] x{D}ial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark, Zhang et al., Findings of the Association for Computational Linguistics: EMNLP 2023

[July, 2023] Don{'}t Forget Your {ABC}{'}s: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems, Finch et al., Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

[May, 2022] Human Evaluation of Conversations is an Open Problem: comparing the sensitivity of various methods for evaluating dialogue agents, Smith et al., Proceedings of the 4th Workshop on NLP for Conversational AI

[August, 2021] {D}yna{E}val: Unifying Turn and Dialogue Level Evaluation, Zhang et al., Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

[January, 2021] Survey on evaluation methods for dialogue systems, Jan Deriu et al., Artificial Intelligence Review

[July, 2020] Towards Unified Dialogue System Evaluation: A Comprehensive Analysis of Current Evaluation Protocols, Finch et al., Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue

[July, 2020] u{BLEU}: Uncertainty-Aware Automatic Evaluation Method for Open-Domain Dialogue Systems, Tsuta et al., Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop

Evaluating embodied social agents

[December, 2022] Don't Copy the Teacher: Data and Model Challenges in Embodied Dialogue, Min et al., EMNLP

[March, 2024] Embodied LLM Agents Learn to Cooperate in Organized Teams, Xudong Guo et al., arXiv

[Februrary, 2021] SocNavBench: A Grounded Simulation Testing Framework for Evaluating Social Navigation Biswas et al., ACM Transactions on Human-Robot Interaction

[January, 2021] Evaluating the Robustness of Collaborative Agents Knott et al., AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems

Evaluating virtual social agents

[January, 2022] The Artificial-Social-Agent Questionnaire: Establishing the long and short questionnaire versions, Siska Fitrianie et al., Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents

[January, 2021] Empathy and prosociality in social agents, Ana Paiva et al., The Handbook on Socially Interactive Agents: 20 Years of Research on Embodied Conversational Agents, Intelligent Virtual Agents, and Social Robotics Volume 1: Methods, Behavior, Cognition

[February, 2020] Embedding Conversational Agents into AR: Invisible or with a Realistic Human Body?, Jens Reinhardt et al., Proceedings of the Fourteenth International Conference on Tangible, Embedded, and Embodied Interaction

[January, 2020] The 19 unifying questionnaire constructs of artificial social agents: An iva community analysis, Siska Fitrianie et al., Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents

[June, 2019] Social-iq: A question answering benchmark for artificial social intelligence, Amir Zadeh et al., Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

[May, 2019] Exploring Virtual Agents for Augmented Reality, Isaac Wang et al., CHI

[July, 2018] Multimodal language analysis in the wild: Cmu-mosei dataset and interpretable dynamic fusion graph, AmirAli Bagher Zadeh et al., Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Evaluating robotics in social contexts

[March, 2024] HumanoidBench: Simulated Humanoid Benchmark for Whole-Body Locomotion and Manipulation, Carmelo Sferrazza et al., arXiv

[December, 2020] Optimization of criterion for objective evaluation of HRI performance that approximates subjective evaluation: a case study in robot competition, Y. Mizuchi et al., Advanced Robotics

[July, 2020] Safety bounds in human robot interaction: A survey, Angeliki Zacharaki et al., Safety science

[December, 2015] RoboCup@ Home: Analysis and results of evolving competitions for domestic and service robots, Luca Iocchi et al., Artificial Intelligence

[October, 2011] A meta-analysis of factors affecting trust in human-robot interaction, Peter A Hancock et al., Human factors

[November, 2009] Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots, Christoph Bartneck et al., International journal of social robotics

[March, 2006] Common metrics for human-robot interaction, Aaron Steinfeld et al., Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction

[January, 2003] Theory and evaluation of human robot interactions, J. Scholtz et al., 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the

Interactions with humans

Human-Chatbot Interaction

[April, 2023] Collaborating with a Text-Based Chatbot: An Exploration of Real-World Collaboration Strategies Enacted during Human-Chatbot Interactions, Amon Rapp et al., Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

[March, 2024] AI Comes Out of the Closet: Using AI-Generated Virtual Characters to Help Individuals Practice LGBTQIA+ Advocacy, Daniel Pillis et al., Proceedings of the 29th International Conference on Intelligent User Interfaces

[April, 2023] Exploring effects of chatbot-based social contact on reducing mental illness stigma, Yi-Chieh Lee et al., Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

[May, 2024] " It's the only thing I can trust": Envisioning Large Language Model Use by Autistic Workers for Communication Assistance, JiWoong Jang et al., Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems

[April, 2022] User perceptions of extraversion in chatbots after repeated use, Sarah Theres V{"o}lkel et al., Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

[September, 2022] Interacting with a chatbot-based advising system: Understanding the effect of chatbot personality and user gender on behavior, Mohammad Amin Kuhail et al., Informatics

[May, 2023] Decision-oriented dialogue for human-ai collaboration, Jessy Lin et al., arXiv preprint arXiv:2305.20076

[May, 2023] The Effects of Engaging and Affective Behaviors of Virtual Agents in Group Decision-Making, Hanseob Kim et al., Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems

[March, 2024] Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration, Crystal Qian et al., Proceedings of the 29th International Conference on Intelligent User Interfaces

Human-Embodied Agent Interaction

[January, 2023] NOPA: Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistants, Puig et al., ICRA

[Januaray, 2021] WATCH-AND-HELP: A CHALLENGE FOR SOCIAL PERCEPTION AND HUMAN-AI COLLABORATION, Puig et al., ICLR

[October, 2019] On the utility of learning about humans for human-ai coordination, Carroll et al., Neurips

[May, 2021] Interaction Flexibility in Artificial Agents Teaming with Human, Nalepka et al., Proceedings of the Annual Meeting of the Cognitive Science Society

[December, 2023] LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordination, Liu et al., arxiv

[May, 2023] Adaptive coordination in social embodied rearrangement, Szot et al., ICML

[April, 2023] Generative Agents: Interactive Simulacra of Human Behavior, Park et al., UIST

[December, 2023] Diverse Conventions for Human-AI Collaboration, Bidipta Sarkar et al., Advances in Neural Information Processing Systems

Human Robot Interaction

[March, 2024] Generative expressive robot behaviors using large language models, Karthik Mahadevan et al., Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction

[October, 2023] Eureka: Human-level reward design via coding large language models, Yecheng Jason Ma et al., arXiv preprint arXiv:2310.12931

[August, 2023] Gesture-informed robot assistance via foundation models, Li-Heng Lin et al., 7th Annual Conference on Robot Learning

[July, 2023] Open problems and fundamental limitations of reinforcement learning from human feedback, Stephen Casper et al., arXiv preprint arXiv:2307.15217

[July, 2023] Robots that ask for help: Uncertainty alignment for large language model planners, Allen Z Ren et al., arXiv preprint arXiv:2307.01928

[June, 2023] Language to rewards for robotic skill synthesis, Wenhao Yu et al., arXiv preprint arXiv:2306.08647

[March, 2023] No, to the right: Online language corrections for robotic manipulation via shared autonomy, Yuchen Cui et al., Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction

[March, 2023] In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing, Lorenzo Shaikewitz et al., International Conference on Robotics and Automation (ICRA)

[March, 2023] Few-shot preference learning for human-in-the-loop rl, Donald Joseph Hejna III et al., Conference on Robot Learning

[August, 2021] Formalizing and guaranteeing human-robot interaction, Hadas Kress-Gazit et al., Communications of the ACM

[October, 2021] Core elements of social interaction for constructive human-robot interaction, Mike EU Ligthart et al., arXiv preprint arXiv:2110.04054

[9, 2021] Modeling user empathy elicited by a robot storyteller, Leena Mathur et al., 2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)

[August, 2021] Formalizing and guaranteeing human-robot interaction, Hadas Kress-Gazit et al., Communications of the ACM

[8, 2021] A theory of social agency for human-robot interaction, Ryan Blake Jackson et al., Frontiers in Robotics and AI

[January, 2021] A taxonomy of social errors in human-robot interaction, Leimin Tian et al., ACM Transactions on Human-Robot Interaction (THRI)

[January, 2021] Turn-taking in conversational systems and human-robot interaction: a review, Gabriel Skantze et al., Computer Speech & Language

[January, 2020] Measuring the perceived social intelligence of robots, Kimberly A Barchard et al., ACM Transactions on Human-Robot Interaction (THRI)

[January, 2017] Enabling robotic social intelligence by engineering human social-cognitive mechanisms, Travis J Wiltshire et al., Cognitive Systems Research

[8, 2005] Effects of nonverbal communication on efficiency and robustness in human-robot teamwork, Cynthia Breazeal et al., 2005 IEEE/RSJ international conference on intelligent robots and systems

[6, 2005] Defining socially assistive robotics, David Feil-Seifer et al., 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005.

[5, 2004] Social interactions in HRI: the robot view, Cynthia Breazeal et al., IEEE transactions on systems, man, and cybernetics, part C (applications and reviews)

[1, 2004] Designing sociable robots, Cynthia Breazeal et al., Designing sociable robots

[1, 1998] A motivational system for regulating human-robot interaction, Cynthia Breazeal et al., AAAI

Human-Human Interaction

[October, 2024] From {Text} to {Self}: {Users}' {Perceptions} of {Potential} of {AI} on {Interpersonal} {Communication} and {Self}, Yue Fu et al., arXiv

[4, 2024] Modeling Multimodal Social Interactions: New Challenges and Baselines with Densely Aligned Representations, Sangmin Lee et al., arXiv preprint arXiv:2403.02090

[April, 2024] Social Skill Training with Large Language Models, Diyi Yang et al., arXiv preprint arXiv:2404.04204

[February, 2024] {IMBUE}: {Improving} {Interpersonal} {Effectiveness} through {Simulation} and {Just}-in-time {Feedback} with {Human}-{Language} {Model} {Interaction}, Inna Wanyin Lin et al., arXiv

[January, 2024] Help {Me} {Reflect}: {Leveraging} {Self}-{Reflection} {Interface} {Nudges} to {Enhance} {Deliberativeness} on {Online} {Deliberation} {Platforms}, Shun Yi Yeo et al., arXiv

[October, 2023] Leveraging {AI} for democratic discourse: {Chat} interventions can improve online political conversations at scale, Lisa P. Argyle et al., Proceedings of the National Academy of Sciences

[January, 2023] A Comprehensive Review of Data-Driven Co-Speech Gesture Generation, Simbarashe Nyatsanga et al., Computer Graphics Forum

[January, 2023] Human–{AI} collaboration enables more empathic conversations in text-based peer-to-peer mental health support, Ashish Sharma et al., Nature Machine Intelligence

[November, 2022] Thread {With} {Caution}: {Proactively} {Helping} {Users} {Assess} and {Deescalate} {Tension} in {Their} {Online} {Discussions}, Jonathan P. Chang et al., Proceedings of the ACM on Human-Computer Interaction

[April, 2021] {AI}-{Mediated} {Communication}: {Language} {Use} and {Interpersonal} {Effects} in a {Referential} {Communication} {Task}, Hannah Mieczkowski et al., Proceedings of the ACM on Human-Computer Interaction

Challenges

Theory of Mind

Social Learning

Simultaneous Interaction

Applications

Health

[March, 2024] Polaris: A Safety-focused LLM Constellation Architecture for Healthcare, Subhabrata Mukherjee et al., arXiv

[January, 2024] Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias, Yu He Ke et al., arXiv

[February, 2024] Benchmarking Large Language Models on Communicative Medical Coaching: a Novel System and Dataset, Hengguan Huang et al., arXiv

[February, 2024] AI Hospital: Interactive Evaluation and Collaboration of LLMs as Intern Doctors for Clinical Diagnosis, Zhihao Fan et al., arXiv

[February, 2024] COCOA: CBT-based Conversational Counseling Agent using Memory Specialized in Cognitive Distortions and Dynamic Prompt, Suyeon Lee et al., arXiv

[May, 2023] Helping the Helper: Supporting Peer Counselors via AI-Empowered Practice and Feedback, Shang-Ling Hsu et al., arXiv

[May, 2023] Read, Diagnose and Chat: Towards Explainable and Interactive LLMs-Augmented Depression Detection in Social Media, Wei Qin et al., arXiv

[May, 2023] An artificial intelligence-based chatbot for prostate cancer education: Design and patient evaluation study, Magdalena Görtz et al., Digital Health

[October, 2024] Conversational Health Agents: A Personalized LLM-Powered Agent Framework, Mahyar Abbasian et al., arXiv

[January, 2023] Foundation models for generalist medical artificial intelligence, Michael Moor et al., Nature

[8, 2022] Can robots help in the evaluation of mental wellbeing in children? an empirical study, Nida Itrat Abbasi et al., 2022 31st IEEE international conference on robot and human interactive communication (RO-MAN)

[January, 2022] Health-related applications of socially interactive agents, Timothy Bickmore et al., The Handbook on Socially Interactive Agents: 20 years of Research on Embodied Conversational Agents, Intelligent Virtual Agents, and Social Robotics Volume 2: Interactivity, Platforms, Application

[January, 2021] Intelligent sensing technologies for the diagnosis, monitoring and therapy of alzheimer’s disease: A systematic review, Nazia Gillani et al., Sensors

[January, 2021] Patients’ perceptions toward human--artificial intelligence interaction in health care: experimental study, Pouyan Esmaeilzadeh et al., Journal of medical Internet research

[January, 2020] The effectiveness of artificial intelligence conversational agents in health care: systematic review, Madison Milne-Ives et al., Journal of medical Internet research

[January, 2019] Artificial intelligence in healthcare robots: A social informatics study of knowledge embodiment, Loo G Pee et al., Journal of the Association for Information Science and Technology

[6, 2018] Personalized machine learning for robot perception of affect and engagement in autism therapy, Ognjen Rudovic et al., Science Robotics

[6, 2013] A socially assistive robot exercise coach for the elderly, Juan Fasola et al., Journal of Human-Robot Interaction

[8, 2012] Robots for use in autism research, Brian Scassellati et al., Annual review of biomedical engineering

Policy

[August, 2022] Social Simulacra: Creating Populated Prototypes for Social Computing Systems, Joon Sung Park et al., Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology

[November, 2024] Do LLMs exhibit human-like response biases? A case study in survey design, Lindia Tjuatja et al., arXiv

[February, 2024] Large language models cannot replace human participants because they cannot portray identity groups, Angelina Wang et al., arXiv

[February, 2024] Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation, Xinyi Mou et al., arXiv

[December, 2023] Language agents as digital representatives in collective decision-making, Daniel Jarrett et al., NeurIPS 2023 Foundation Models for Decision Making Workshop

[March, 2024] From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News, Yuhan Liu et al., arXiv

Education

[6, 2024] How to Teach Programming in the {AI} Era? Using {LLM}s as a Teachable Agent for Debugging, Qianou Ma et al., International Conference on Artificial Intelligence in Education

[6, 2024] Generating Situated Reflection Triggers About Alternative Solution Paths: A Case Study in Generative {AI} for Computer-Supported Collaborative Learning, Atharva Naik et al., International Conference on Artificial Intelligence in Education

[01, 2024] {CodeAid}: Evaluating a Classroom Deployment of an {LLM-based} Programming Assistant that Balances Student and Educator Needs, Majeed Kazemitabaar et al., arXiv

[01, 2024] Learning Agent-based Modeling with {LLM} Companions: Experiences of Novices and Experts Using {ChatGPT} & {NetLogo} Chat, John Chen et al., arXiv

[11, 2023] {AI-TA}: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source {LLMs}, Yann Hicke et al., arXiv

[10, 2023] {Ruffle&Riley}: Towards the Automated Induction of Conversational Tutoring Systems, Robin Schmucker et al., arXiv

[09, 2023] Teach {AI} How to Code: Using Large Language Models as Teachable Agents for Programming Education, Hyoungwook Jin et al., arXiv

[7, 2023] {GPTeach}: Interactive {TA} Training with {GPT-based} Students, Julia M Markel et al., Proceedings of the Tenth {ACM} Conference on Learning @ Scale

[05, 2023] {CLASS} Meet {SPOCK}: An Education Tutoring Chatbot based on Learning Science Principles, Shashank Sonkar et al., arXiv

[1, 2023] AI for Students with Learning Disabilities: A Systematic Review, Xiaoming Zhai et al., n/a

[5, 2022] Designing {PairBuddy---A} Conversational Agent for Pair Programming, Peter Robe et al., ACM Trans. Comput.-Hum. Interact.

[6, 2021] Going Online: A Simulated Student Approach for Evaluating Knowledge Tracing in the Context of Mastery Learning, Qiao Zhang et al., International Educational Data Mining Society

[6, 2020] Investigating differential error types between human and simulated learners, D Weitekamp et al., Artif. Intell.

[3, 2016] Affective personalization of a social robot tutor for children’s second language skills, Goren Gordon et al., Proceedings of the AAAI conference on artificial intelligence

[11, 2013] Cognitive anatomy of tutor learning: Lessons learned with {SimStudent}, Noboru Matsuda et al., J. Educ. Psychol.

[7, 2013] How Effective are Pedagogical Agents for Learning? A {Meta-Analytic} Review, Noah L Schroeder et al., Journal of Educational Computing Research

[4, 1985] Intelligent tutoring systems, J R Anderson et al., Science

Concerns

Risks

[2, 2024] The potential of generative AI for personalized persuasion at scale, SC Matz et al., Scientific Reports

[2, 2024] Jailbroken: How does llm safety training fail?, Alexander Wei et al., Advances in Neural Information Processing Systems

[01, 2024] Two Types of AI Existential Risk: Decisive and Accumulative, Atoosa Kasirzadeh et al., arXiv

[12, 2023] Llama guard: Llm-based input-output safeguard for human-ai conversations, Hakan Inan et al., arXiv preprint arXiv:2312.06674

[10, 2023] Characterizing manipulation from AI systems, Micah Carroll et al., Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization

[9, 2023] The rise and potential of large language model based agents: A survey, Zhiheng Xi et al., arXiv preprint arXiv:2309.07864

[7, 2023] Voice in the machine: Ethical considerations for language-capable robots, Tom Williams et al., Communications of the ACM

[03, 2023] Artificial Influence: An Analysis Of AI-Driven Persuasion, Matthew Burtell et al., arXiv

[10, 2022] "Playing God": How the Metaverse Will Challenge Our Very Notion of Free Will, Louis Rosenberg et al., Big Think

[9, 2022] Risk and Exposure of XAI in Persuasion and Argumentation: The case of Manipulation, Rachele Carli et al., International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems

[12, 2021] Risks from AI Persuasion, Beth Barnes et al., AI Alignment Forum

[12, 2021] Good robots, bad robots: Morally valenced behavior effects on perceived mind, morality, and trust, Jaime Banks et al., International Journal of Social Robotics

[6, 2021] Bad machines corrupt good morals, Nils K{"o}bis et al., Nature Human Behaviour

[3, 2021] On the dangers of stochastic parrots: Can language models be too big?🦜, Emily M Bender et al., Proceedings of the 2021 ACM conference on fairness, accountability, and transparency

[02, 2021] The corruptive force of AI-generated advice, Margarita Leib et al., arXiv

[11, 2020] Persuasion Tools: AI Takeover Without AGI or Agency?, Daniel Kokotajlo et al., AI Alignment Forum

[9, 2020] Realtoxicityprompts: Evaluating neural toxic degeneration in language models, Samuel Gehman et al., arXiv preprint arXiv:2009.11462

[2, 2020] Artificial intelligence crime: An interdisciplinary analysis of foreseeable threats and solutions, Thomas C King et al., Science and engineering ethics

[3, 2019] Language-capable robots may inadvertently weaken human moral norms, Ryan Blake Jackson et al., 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

[12, 2011] 13 The inherent dangers of unidirectional emotional bonds between humans and social robots, Matthias Scheutz et al., Robot ethics: The ethical and social implications of robotics

[8, 2004] On the morality of artificial agents, Luciano Floridi et al., Minds and machines

Safety

[04, 2024] Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Generative Agents, Seth Lazar et al., arXiv

[1, 2024] Deception and Manipulation in Generative AI, Christian Tarsney et al., ArXiv

[12, 2023] Social Contract AI: Aligning AI Assistants with Implicit Group Norms, Jan-Philipp Fr{"a}nken et al., Socially Responsible Language Modelling Research

[10, 2023] Towards Understanding Sycophancy in Language Models, Mrinank Sharma et al., ArXiv

[09, 2023] Identifying the Risks of LM Agents with an LM-Emulated Sandbox, Yangjun Ruan et al., arXiv

[8, 2023] AI Deception: A Survey of Examples, Risks, and Potential Solutions, Peter S. Park et al., ArXiv

[06, 2023] An Overview of Catastrophic AI Risks, Dan Hendrycks et al., arXiv

[5, 2023] Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting, Miles Turpin et al., ArXiv

[12, 2022] Understanding Stereotypes in Language Models: Towards Robust Measurement and Zero-Shot Debiasing, Justus Mattern et al., ArXiv

[12, 2022] Constitutional AI: Harmlessness from AI Feedback, Yuntao Bai et al., ArXiv

[6, 2022] Predictability and surprise in large generative models, Deep Ganguli et al., Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency

[3, 2022] Teaching language models to support answers with verified quotes, Jacob Menick et al., arXiv preprint arXiv:2203.11147

[12, 2021] Ethical and social risks of harm from language models, Laura Weidinger et al., arXiv preprint arXiv:2112.04359

[10, 2021] Can machines learn morality? the delphi experiment, Liwei Jiang et al., arXiv preprint arXiv:2110.07574

[9, 2021] Truthfulqa: Measuring how models mimic human falsehoods, Stephanie Lin et al., arXiv preprint arXiv:2109.07958

[6, 2021] Towards Understanding and Mitigating Social Biases in Language Models, Paul Pu Liang et al., International Conference on Machine Learning

[10, 2020] Aligning ai with shared human values, Dan Hendrycks et al., arXiv preprint arXiv:2008.02275

[10, 2020] Recipes for safety in open-domain chatbots, Jing Xu et al., arXiv preprint arXiv:2010.07079

[9, 2020] Measuring massive multitask language understanding, Dan Hendrycks et al., arXiv preprint arXiv:2009.03300

[12, 2018] Ethical challenges in data-driven dialogue systems, Peter Henderson et al., Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society

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A collection of works that investigate social agents, simulations and their real-world impact in text, embodied, and robotics contexts.

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