Awesome-LLM-Computational-Argumentation

The Hub of Computational Argumentation in the Era of LLM, where you can find surveys, papers, datasets, benchmarks, and evaluations of commonly used LLMs on computational Argumentation tasks.

Table of Contents

• Awesome-LLM-Computational-Argumentation
  • Table of Contents
  • Evaluation
  • Benchmark & datasets
  • Survey
  • Papers
    • Argument Mining
    • Argument Generation
    • Quality Assessment
    • Debate For LLM
  • Contributing

Evaluation

Benchmark & datasets

Date	Paper	Publication
2024-08	DebateQA: Evaluating Question Answering on Debatable Knowledge	Arxiv
2024-06	Assessing Good, Bad and Ugly Arguments Generated by ChatGPT: a New Dataset, its Methodology and Associated Tasks	EPIA 2023
2024-06	Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluation	ACL 2024
2024-06	OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset	ACL 2024
2024-02	Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements	ACL 2024
2023-12	FREDSum: A Dialogue Summarization Corpus for French Political Debates	EMNLP2023
2023-11	Automatic Analysis of Substantiation in Scientific Peer Reviews	EMNLP 2023
2022-06	QT30: A Corpus of Argument and Conflict in Broadcast Debate	ACL 2022
2022-04	Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions	ACL 2022
2022-03	IAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Tasks	ACL
2021-02	SummEval: Re-evaluating Summarization Evaluation	tacl
2021-01	Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale	EACL 2021
2020-12	Transformer-Based Argument Mining for Healthcare Applications	ECAI 2020
2020-10	Detecting Attackable Sentences in Arguments	EMNLP 2020
2020-10	Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains	EMNLP
2020-06	Rhetoric, Logic, and Dialectic: Advancing Theory-based Argument Quality Assessment in Natural Language Processing	COLING
2020-05	USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation	ACL 2020
2019-09	A Dataset of General-Purpose Rebuttal	EMNLP 2019
2019-06	Exploring the Role of Prior Beliefs for Argument Persuasion	ACL 2018
2019-06	A Corpus for Modeling User and Language Effects in Argumentation on Online Debating	ACL
2018-02	Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks	EMNLP
2017-04	Recognizing Insufficiently Supported Arguments in Argumentative Essays	EACL
2016-04	Parsing Argumentation Structures in Persuasive Essays	Computational Linguistics

Survey

Date	Paper	Publication
2023-11	Exploring the Potential of Large Language Models in Computational Argumentation	ACL

Papers

Argument Mining

Date	Paper	Publication
2024-07	Argument Mining in Data Scarce Settings: Cross-lingual Transfer and Few-shot Techniques	ACL 2024
2024-06	In-Context Learning and Fine-Tuning GPT for Argument Mining	Arxiv
2024-05	WIBA: What Is Being Argued? A Comprehensive Approach to Argument Mining	ASONAM
2024-05	DMON: A Simple yet Effective Approach for Argument Structure Learning	COLING 2024
2024-04	Exploring Key Point Analysis with Pairwise Generation and Graph Partitioning	NAACL 2024
2024-04	A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality	NAACL 2024
2024-04	TACO -- Twitter Arguments from COnversations	Arxiv
2024-02	Can Large Language Models perform Relation-based Argument Mining?	ACL 2024
2024-01	End-to-End Argument Mining over Varying Rhetorical Structures	Arxiv
2023-12	Hi-ArG: Exploring the Integration of Hierarchical Argumentation Graphs in Language Pretraining	EMNLP 2023
2023-10	Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining	EMNLP
2023-10	TILFA: A Unified Framework for Text, Image, and Layout Fusion in Argument Mining	EMNLP 2023
2023-06	Detecting Check-Worthy Claims in Political Debates, Speeches, and Interviews Using Audio Data	ICASSP
2023-05	AQE: Argument Quadruplet Extraction via a Quad-Tagging Augmented Generative Approach	ACL 2023
2023-02	VivesDebate-Speech: A Corpus of Spoken Argumentation to Leverage Audio Features for Argument Mining	EMNLP 2023
2022-09	Perturbations and Subpopulations for Testing Robustness in Token-Based Argument Unit Recognition	COLING 2022
2022-09	ImageArg: A Multi-modal Tweet Dataset for Image Persuasiveness Mining	COLING
2022-05	A Holistic Framework for Analyzing the COVID-19 Vaccine Debate	NAACL 2022
2022-04	Echoes through Time: Evolution of the Italian COVID-19 Vaccination Debate	AAAI
2022-03	Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?	ACL 2022

Argument Generation

Date	Paper	Publication
2024-06	Persuasiveness of Generated Free-Text Rationales in Subjective Decisions: A Case Study on Pairwise Argument Ranking	Arxiv
2023-12	Argue with Me Tersely: Towards Sentence-Level Counter-Argument Generation	EMNLP 2023
2023-10	From Values to Opinions: Predicting Human Behaviors and Stances Using Value-Injected Large Language Models	EMNLP 2023
2023-09	Claim Optimization in Computational Argumentation	INLG 2023
2023-07	DebateKG: Automatic Policy Debate Case Creation with Semantic Knowledge Graphs	EMNLP 2023
2023-01	Conclusion-based Counter-Argument Generation	eacl-23
2022-10	MOCHA: A Multi-Task Training Approach for Coherent Text Generation from Cognitive Perspective	EMNLP 2022
2022-05	RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators	NAACL 2022
2022-03	The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments	ACL 2022

Quality Assessment

Date	Paper	Publication
2024-06	Assessing Good, Bad and Ugly Arguments Generated by ChatGPT: a New Dataset, its Methodology and Associated Tasks	EPIA 2023
2024-04	Can Language Models Recognize Convincing Arguments?	Arxiv
2024-03	Argument Quality Assessment in the Age of Instruction-Following Large Language Models	COLING 2024
2023-11	Automatic Analysis of Substantiation in Scientific Peer Reviews	EMNLP 2023
2023-05	Contextualizing Argument Quality Assessment with Relevant Knowledge	NAACL 2024
2023-01	Conclusion-based Counter-Argument Generation	eacl-23
2022-12	Claim Optimization in Computational Argumentation	INLG 2023
2022-03	Automatic Debate Evaluation with Argumentation Semantics and Natural Language Argument Graph Networks	EMNLP 2023
2021-10	Assessing the Sufficiency of Arguments through Conclusion Generation	EMNLP 2021
2020-12	Rhetoric, Logic, and Dialectic: Advancing Theory-based Argument Quality Assessment in Natural Language Processing	COLING 20
2020-10	Exploring the Role of Argument Structure in Online Debate Persuasion	EMNLP 2020
2019-09	A Large-scale Dataset for Argument Quality Ranking: Construction and Analysis	AAAI 2020
2019-09	Automatic Argument Quality Assessment -- New Datasets and Methods	EMNLP 2019

Debate For LLM

Date	Paper	Publication
2024-08	Can LLMs Beat Humans in Debating? A Dynamic Multi-agent Framework for Competitive Debate	Arxiv
2024-06	An Empirical Analysis on Large Language Models in Debate Evaluation	ACL 2024
2024-05	DEBATE: Devil's Advocate-Based Assessment and Text Evaluation	Arxiv
2024-03	Debatrix: Multi-dimensional Debate Judge with Iterative Chronological Analysis Based on LLM	ACL 2024
2024-03	A Picture Is Worth a Graph: A Blueprint Debate Paradigm for Multimodal Reasoning	ACM Multimedia
2024-02	Debating with More Persuasive LLMs Leads to More Truthful Answers	ICML 2024
2024-02	Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements	ACL 2024
2024-01	Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate	Arxiv
2024-01	Combating Adversarial Attacks with Multi-Agent Debate	Arxiv
2024-01	Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models	ACM Web
2023-12	Learning to Break: Knowledge-Enhanced Reasoning in Multi-Agent Debate System	Arxiv
2023-12	Recourse under Model Multiplicity via Argumentative Ensembling (Technical Report)	AAMAS 2024
2023-11	Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs	Arixv
2023-11	Debate Helps Supervise Unreliable Experts	Arxiv
2023-11	Scalable AI Safety via Doubly-Efficient Debate	Arxiv
2023-10	From Values to Opinions: Predicting Human Behaviors and Stances Using Value-Injected Large Language Models	EMNLP 2023
2023-10	Let Models Speak Ciphers: Multiagent Debate through Embeddings	ICLR 2024
2023-08	ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate	ICLR 2024
2023-05	Can ChatGPT Defend its Belief in Truth? Evaluating LLM Reasoning via Debate	EMNLP 2023
2023-05	Improving Factuality and Reasoning in Language Models through Multiagent Debate	ICML 2024
2023-05	Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate	Arxiv
2023-05	Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate	EMNLP 2023
2022-10	The Debate Over Understanding in AI's Large Language Models	Arixv
2022-03	The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments	ACL 2022
2021-10	Project Debater APIs: Decomposing the AI Grand Challenge	EMNLP 2021

Contributing