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# Who cites «Abductive Commonsense Reasoning»

274 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/bhagavatula-2019-abductive-commonsense-reasoning/)

Pages: **1** · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bhagavatula-2019-abductive-commonsense-reasoning-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bhagavatula-2019-abductive-commonsense-reasoning-3/)

1. [Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility](https://aclanthology.org/2026.acl-long.599/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
2. [DIXITWORLD: Evaluating Multimodal Abductive Reasoning in Vision-Language Models with Multi-Agent Dixit Gameplay](https://aclanthology.org/2026.acl-short.37/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
3. [Decoupling the Effect of Chain-of-Thought Reasoning: A Human Label Variation Perspective](https://aclanthology.org/2026.findings-acl.1103/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
4. [EVADE: LLM-Based Explanation Generation and Validation for Error Detection in NLI](https://aclanthology.org/2026.findings-acl.65/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
5. [HCMUS RepeatedGames at SemEval-2026 Task 12: CausalRAG: Synergizing Causal Graph Retrieval and Extended LoRA for Abductive Reasoning](https://aclanthology.org/2026.semeval-1.59/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
6. [KDW at SemEval-2026 Task 12: Logic-Driven Distillation with Knowledge Graphs for Efficient Abductive Reasoning](https://aclanthology.org/2026.semeval-1.124/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
7. [Knowledge Vector of Logical Reasoning in Large Language Models](https://aclanthology.org/2026.acl-long.2021/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
8. [Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden States](https://aclanthology.org/2026.trustnlp-main.12/) *— 2026 · Proceedings of the 6th Workshop on Trustworthy NLP (TrustNLP 2026)*
9. [OseiBrefo-Liang at SemEval-2026 Task 12: Hybrid Causal Knowledge Graphs and Neural-Symbolic Policy Optimisation for Abductive Event Reasoning](https://aclanthology.org/2026.semeval-1.287/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
10. [SemEval-2026 Task 12: Abductive Event Reasoning: Towards Real-World Event Causal Inference for Large Language Models](https://aclanthology.org/2026.semeval-1.446/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
11. [SemEval-2026 Task 12: Knowledge Graph with hyperbolic embedding in Abductive Event Reasoning](https://aclanthology.org/2026.semeval-1.114/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
12. [Social Story Frames: Contextual Reasoning about Narrative Intent and Reception](https://aclanthology.org/2026.acl-long.1934/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
13. [Synthetic Data Generation for Training Diversified Commonsense Reasoning Models](https://aclanthology.org/2026.acl-long.1520/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [The Validity of Coreference-based Evaluations of Natural Language Understanding](https://arxiv.org/abs/2602.16200) *— 2026 · arXiv:2602.16200*
15. [Vinclat: Evaluating Reasoning, Cognition and Culture in One Game](https://aclanthology.org/2026.mme-main.4/) *— 2026 · Proceedings of the First Workshop on Multilingual Multicultural Evaluation*
16. [X-NLP at SemEval-2026 Task 12: Prompting LLMs for Abductive Event Reasoning](https://aclanthology.org/2026.semeval-1.289/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
17. [YNU-HPCC at SemEval-2026 Task 12: Retrieval-Guided Reasoning with Teacher Distillation for Abductive Event Reasoning](https://aclanthology.org/2026.semeval-1.30/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
18. [d-itlab at SemEval-2026 Task 12: Per-Option Surprisal and Multi-Stage Gating for Precision-Oriented Causal Reasoning](https://aclanthology.org/2026.semeval-1.228/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
19. [sutta at SemEval-2026 Task 12: A Multi-Perspective Retrieve-Verify-Aggregate Framework for Abductive Event Reasoning](https://aclanthology.org/2026.semeval-1.323/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
20. [CausalEval: Towards Better Causal Reasoning in Language Models](https://aclanthology.org/2025.naacl-long.622/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
21. [Entailed Between the Lines: Incorporating Implication into NLI](https://aclanthology.org/2025.acl-long.1552/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
22. [From Reasoning to Learning: A Survey on Hypothesis Discovery and Rule Learning with Large Language Models](https://arxiv.org/abs/2505.21935) *— 2025 · arXiv:2505.21935*
23. [Let''s CONFER: A Dataset for Evaluating Natural Language Inference Models on CONditional InFERence and Presupposition](https://arxiv.org/abs/2506.06133) *— 2025 · arXiv:2506.06133*
24. [Lost in Inference: Rediscovering the Role of Natural Language Inference for Large Language Models](https://aclanthology.org/2025.naacl-long.466/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
25. [MMTEB: Massive Multilingual Text Embedding Benchmark](https://arxiv.org/abs/2502.13595) *— 2025 · arXiv:2502.13595*
26. [On the Role of Entity and Event Level Conceptualization in Generalizable Reasoning: A Survey of Tasks, Methods, Applications, and Future Directions](https://aclanthology.org/2025.findings-emnlp.122/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
27. [Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos](https://arxiv.org/abs/2506.05302) *— 2025 · arXiv:2506.05302*
28. [STRICTA: Structured Reasoning in Critical Text Assessment for Peer Review and Beyond](https://aclanthology.org/2025.acl-long.1107/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
29. [The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models](https://aclanthology.org/2025.naacl-long.303/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
30. [Aquila2 Technical Report](https://arxiv.org/abs/2408.07410) *— 2024 · arXiv:2408.07410*
31. [Are LLMs classical or nonmonotonic reasoners? Lessons from generics](https://aclanthology.org/2024.acl-short.51/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
32. [Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?](https://aclanthology.org/2024.acl-long.555/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
33. [Belief Revision: The Adaptability of Large Language Models Reasoning](https://aclanthology.org/2024.emnlp-main.586/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
34. [CANDLE: Iterative Conceptualization and Instantiation Distillation from Large Language Models for Commonsense Reasoning](https://aclanthology.org/2024.acl-long.128/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
35. [CLOMO: Counterfactual Logical Modification with Large Language Models](https://aclanthology.org/2024.acl-long.593/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
36. [Complex Reasoning over Logical Queries on Commonsense Knowledge Graphs](https://aclanthology.org/2024.acl-long.613/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
37. [DetermLR: Augmenting LLM-based Logical Reasoning from Indeterminacy to Determinacy](https://aclanthology.org/2024.acl-long.531/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
38. [Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA](https://aclanthology.org/2024.emnlp-main.1201/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
39. [Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus](https://arxiv.org/abs/2411.12498) *— 2024 · arXiv:2411.12498*
40. [Epistemology of Language Models: Do Language Models Have Holistic Knowledge?](https://aclanthology.org/2024.findings-acl.751/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
41. [Every Answer Matters: Evaluating Commonsense with Probabilistic Measures](https://aclanthology.org/2024.acl-long.29/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
42. [Exploring Defeasibility in Causal Reasoning](https://aclanthology.org/2024.findings-acl.384/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
43. [Foundational Challenges in Assuring Alignment and Safety of Large Language Models](https://arxiv.org/abs/2404.09932) *— 2024 · arXiv:2404.09932*
44. [Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models](https://aclanthology.org/2024.lrec-main.708/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
45. [How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability?](https://aclanthology.org/2024.tacl-1.63/) *— 2024 · Transactions of the Association for Computational Linguistics*
46. [Improving Language Model Reasoning with Self-motivated Learning](https://aclanthology.org/2024.lrec-main.774/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
47. [Language Models as Inductive Reasoners](https://aclanthology.org/2024.eacl-long.13/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
48. [MOOSE-Chem: Large Language Models for Rediscovering Unseen Chemistry Scientific Hypotheses](https://arxiv.org/abs/2410.07076) *— 2024 · arXiv:2410.07076*
49. [Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance](https://arxiv.org/abs/2403.09085) *— 2024 · arXiv:2403.09085*
50. [Multi-Task Inference: Can Large Language Models Follow Multiple Instructions at Once?](https://aclanthology.org/2024.acl-long.304/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
51. [Multi-Task Learning with Adapters for Plausibility Prediction: Bridging the Gap or Falling into the Trenches?](https://aclanthology.org/2024.insights-1.18/) *— 2024 · Proceedings of the Fifth Workshop on Insights from Negative Results in NLP*
52. [Okay, Let's Do This! Modeling Event Coreference with Generated Rationales and Knowledge Distillation](https://aclanthology.org/2024.naacl-long.218/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
53. [Plausibly Problematic Questions in Multiple-Choice Benchmarks for Commonsense Reasoning](https://aclanthology.org/2024.findings-emnlp.198/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
54. [UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations](https://aclanthology.org/2024.naacl-long.469/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
55. [VariErr NLI: Separating Annotation Error from Human Label Variation](https://aclanthology.org/2024.acl-long.123/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
56. [tasksource: A Large Collection of NLP tasks with a Structured Dataset Preprocessing Framework](https://aclanthology.org/2024.lrec-main.1361/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
57. [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://arxiv.org/abs/2302.04023) *— 2023 · arXiv:2302.04023*
58. [A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target Training](https://aclanthology.org/2023.acl-long.818/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
59. [Abductive Commonsense Reasoning Exploiting Mutually Exclusive Explanations](https://aclanthology.org/2023.acl-long.831/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
60. [Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond](https://arxiv.org/abs/2306.09841) *— 2023 · arXiv:2306.09841*
61. [CALM-Bench: A Multi-task Benchmark for Evaluating Causality-Aware Language Models](https://aclanthology.org/2023.findings-eacl.23/) *— 2023 · Findings of the Association for Computational Linguistics: EACL 2023*
62. [CAR: Conceptualization-Augmented Reasoner for Zero-Shot Commonsense Question Answering](https://aclanthology.org/2023.findings-emnlp.902/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
63. [CAT: A Contextualized Conceptualization and Instantiation Framework for Commonsense Reasoning](https://aclanthology.org/2023.acl-long.733/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
64. [CLadder: Assessing Causal Reasoning in Language Models](https://arxiv.org/abs/2312.04350) *— 2023 · arXiv:2312.04350*
65. [COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective](https://aclanthology.org/2023.acl-long.288/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
66. [CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks](https://aclanthology.org/2023.emnlp-main.607/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
67. [Can Large Language Models Infer Causation from Correlation?](https://arxiv.org/abs/2306.05836) *— 2023 · arXiv:2306.05836*
68. [Cognitive Reframing of Negative Thoughts through Human-Language Model Interaction](https://aclanthology.org/2023.acl-long.555/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
69. [Commonsense Knowledge Transfer for Pre-trained Language Models](https://aclanthology.org/2023.findings-acl.368/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
70. [Commonsense Reasoning for Conversational AI: A Survey of the State of the Art](https://arxiv.org/abs/2302.07926) *— 2023 · arXiv:2302.07926*
71. [Crystal: Introspective Reasoners Reinforced with Self-Feedback](https://aclanthology.org/2023.emnlp-main.708/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
72. [Curing the SICK and Other NLI Maladies](https://aclanthology.org/2023.cl-1.5/) *— 2023 · Computational Linguistics*
73. [Defining a New NLP Playground](https://aclanthology.org/2023.findings-emnlp.799/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
74. [Evaluating and Improving the Coreference Capabilities of Machine Translation Models](https://aclanthology.org/2023.eacl-main.69/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
75. [Evaluating the Rationale Understanding of Critical Reasoning in Logical Reading Comprehension](https://aclanthology.org/2023.emnlp-main.9/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
76. [Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate](https://aclanthology.org/2023.findings-emnlp.508/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
77. [FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets](https://arxiv.org/abs/2307.10928) *— 2023 · arXiv:2307.10928*
78. [Few-shot Adaptation Works with UnpredicTable Data](https://aclanthology.org/2023.acl-long.102/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
79. [Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems](https://arxiv.org/abs/2310.01991) *— 2023 · arXiv:2310.01991*
80. [Gold: A Global and Local-aware Denoising Framework for Commonsense Knowledge Graph Noise Detection](https://aclanthology.org/2023.findings-emnlp.232/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
81. [Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language](https://arxiv.org/abs/2306.02797) *— 2023 · arXiv:2306.02797*
82. [Knowledge Graph Compression Enhances Diverse Commonsense Generation](https://aclanthology.org/2023.emnlp-main.37/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
83. [Knowledge Rumination for Pre-trained Language Models](https://aclanthology.org/2023.emnlp-main.206/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
84. [Large Language Models are Better Reasoners with Self-Verification](https://aclanthology.org/2023.findings-emnlp.167/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
85. [Large Language Models for Generative Information Extraction: A Survey](https://arxiv.org/abs/2312.17617) *— 2023 · arXiv:2312.17617*
86. [Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?](https://aclanthology.org/2023.acl-long.659/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
87. [Less Likely Brainstorming: Using Language Models to Generate Alternative Hypotheses](https://aclanthology.org/2023.findings-acl.794/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
88. [Logical Reasoning over Natural Language as Knowledge Representation: A Survey](https://arxiv.org/abs/2303.12023) *— 2023 · arXiv:2303.12023*
89. [Making Language Models Better Reasoners with Step-Aware Verifier](https://aclanthology.org/2023.acl-long.291/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
90. [Natural Language Reasoning, A Survey](https://arxiv.org/abs/2303.14725) *— 2023 · arXiv:2303.14725*
91. [NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation](https://aclanthology.org/2023.findings-emnlp.80/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
92. [PASTA: A Dataset for Modeling PArticipant STAtes in Narratives](https://aclanthology.org/2023.tacl-1.73/) *— 2023 · Transactions of the Association for Computational Linguistics*
93. [Pre-Training to Learn in Context](https://aclanthology.org/2023.acl-long.267/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
94. [RECKONING: Reasoning through Dynamic Knowledge Encoding](https://arxiv.org/abs/2305.06349) *— 2023 · arXiv:2305.06349*
95. [SETI: Systematicity Evaluation of Textual Inference](https://aclanthology.org/2023.findings-acl.252/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
96. [Self-Consistent Narrative Prompts on Abductive Natural Language Inference](https://aclanthology.org/2023.ijcnlp-main.67/) *— 2023 · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
97. [The Generative AI Paradox: "What It Can Create, It May Not Understand](https://arxiv.org/abs/2311.00059) *— 2023 · arXiv:2311.00059*
98. [The Magic of IF: Investigating Causal Reasoning Abilities in Large Language Models of Code](https://aclanthology.org/2023.findings-acl.574/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
99. [The Web Can Be Your Oyster for Improving Language Models](https://aclanthology.org/2023.findings-acl.46/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
100. [Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models](https://arxiv.org/abs/2310.00836) *— 2023 · arXiv:2310.00836*

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