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# Who cites «Abductive Commonsense Reasoning» · page 2

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/)

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1. [True Detective: A Deep Abductive Reasoning Benchmark Undoable for GPT-3 and Challenging for GPT-4](https://aclanthology.org/2023.starsem-1.28/) *— 2023 · Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)*
2. [Uncovering Implicit Inferences for Improved Relational Argument Mining](https://aclanthology.org/2023.eacl-main.182/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
3. [Unveiling the Multi-Annotation Process: Examining the Influence of Annotation Quantity and Instance Difficulty on Model Performance](https://aclanthology.org/2023.findings-emnlp.96/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
4. [Vera: A General-Purpose Plausibility Estimation Model for Commonsense Statements](https://aclanthology.org/2023.emnlp-main.81/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
5. [A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing](https://aclanthology.org/2022.findings-emnlp.157/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
6. [A Review on Language Models as Knowledge Bases](https://arxiv.org/abs/2204.06031) *— 2022 · arXiv:2204.06031*
7. [A Systematic Investigation of Commonsense Knowledge in Large Language Models](https://aclanthology.org/2022.emnlp-main.812/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
8. [ANLIzing the Adversarial Natural Language Inference Dataset](https://aclanthology.org/2022.scil-1.3/) *— 2022 · Proceedings of the Society for Computation in Linguistics 2022*
9. [AbductionRules: Training Transformers to Explain Unexpected Inputs](https://aclanthology.org/2022.findings-acl.19/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
10. [Aligning Generative Language Models with Human Values](https://aclanthology.org/2022.findings-naacl.18/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
11. [Analytical Reasoning of Text](https://aclanthology.org/2022.findings-naacl.177/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
12. [Analyzing Biases to Spurious Correlations in Text Classification Tasks](https://aclanthology.org/2022.aacl-short.11/) *— 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
13. [Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models](https://arxiv.org/abs/2206.04615) *— 2022 · arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj*
14. [CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues](https://aclanthology.org/2022.acl-long.344/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
15. [Case-Based Abductive Natural Language Inference](https://aclanthology.org/2022.coling-1.134/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
16. [ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification](https://aclanthology.org/2022.acl-long.183/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
17. [Cloze Evaluation for Deeper Understanding of Commonsense Stories in Indonesian](https://aclanthology.org/2022.csrr-1.2/) *— 2022 · Proceedings of the First Workshop on Commonsense Representation and Reasoning (CSRR 2022)*
18. [CoSe-Co: Text Conditioned Generative CommonSense Contextualizer](https://aclanthology.org/2022.naacl-main.83/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
19. [Coalescing Global and Local Information for Procedural Text Understanding](https://aclanthology.org/2022.coling-1.132/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
20. [Diffusion-LM Improves Controllable Text Generation](https://arxiv.org/abs/2205.14217) *— 2022 · arXiv:2205.14217*
21. [DiscoSense: Commonsense Reasoning with Discourse Connectives](https://aclanthology.org/2022.emnlp-main.703/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
22. [Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning](https://aclanthology.org/2022.findings-acl.79/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
23. [Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts](https://aclanthology.org/2022.findings-acl.149/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
24. [Eliciting and Understanding Cross-task Skills with Task-level Mixture-of-Experts](https://aclanthology.org/2022.findings-emnlp.189/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
25. [Forging Multiple Training Objectives for Pre-trained Language Models via Meta-Learning](https://aclanthology.org/2022.findings-emnlp.482/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
26. [GEMv2: Multilingual NLG Benchmarking in a Single Line of Code](https://aclanthology.org/2022.emnlp-demos.27/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
27. [GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation](https://aclanthology.org/2022.emnlp-main.787/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
28. [Hyperdecoders: Instance-specific decoders for multi-task NLP](https://aclanthology.org/2022.findings-emnlp.124/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
29. [ILDAE: Instance-Level Difficulty Analysis of Evaluation Data](https://aclanthology.org/2022.acl-long.240/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
30. [Knowledge-Augmented Methods for Natural Language Processing](https://aclanthology.org/2022.acl-tutorials.3/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts*
31. [Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought](https://arxiv.org/abs/2210.01240) *— 2022 · arXiv:2210.01240*
32. [Leveraging Large Language Models for Multiple Choice Question Answering](https://arxiv.org/abs/2210.12353) *— 2022 · arXiv:2210.12353*
33. [LogicNMR: Probing the Non-monotonic Reasoning Ability of Pre-trained Language Models](https://aclanthology.org/2022.findings-emnlp.265/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
34. [Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension](https://aclanthology.org/2022.coling-1.126/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
35. [Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoning](https://aclanthology.org/2022.naacl-main.163/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
36. [Natural Language Deduction with Incomplete Information](https://aclanthology.org/2022.emnlp-main.564/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
37. [On Curriculum Learning for Commonsense Reasoning](https://aclanthology.org/2022.naacl-main.72/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
38. [On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations](https://aclanthology.org/2022.findings-naacl.168/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
39. [PaCo: Preconditions Attributed to Commonsense Knowledge](https://aclanthology.org/2022.findings-emnlp.505/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
40. [Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios](https://aclanthology.org/2022.coling-1.319/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
41. [Reasoning Like Program Executors](https://aclanthology.org/2022.emnlp-main.48/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
42. [Retrieval Augmentation for Commonsense Reasoning: A Unified Approach](https://aclanthology.org/2022.emnlp-main.294/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
43. [SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer](https://aclanthology.org/2022.acl-long.346/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
44. [Stop Measuring Calibration When Humans Disagree](https://aclanthology.org/2022.emnlp-main.124/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
45. [Task Compass: Scaling Multi-task Pre-training with Task Prefix](https://aclanthology.org/2022.findings-emnlp.416/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
46. [Things not Written in Text: Exploring Spatial Commonsense from Visual Signals](https://aclanthology.org/2022.acl-long.168/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
47. [Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data](https://aclanthology.org/2022.acl-long.226/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
48. [Transferring Confluent Knowledge to Argument Mining](https://aclanthology.org/2022.coling-1.597/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
49. [Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering](https://aclanthology.org/2022.emnlp-main.691/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
50. [UL2: Unifying Language Learning Paradigms](https://arxiv.org/abs/2205.05131) *— 2022 · arXiv:2205.05131*
51. [WordTies: Measuring Word Associations in Language Models via Constrained Sampling](https://aclanthology.org/2022.findings-emnlp.440/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
52. [e-CARE: a New Dataset for Exploring Explainable Causal Reasoning](https://aclanthology.org/2022.acl-long.33/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
53. [minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models](https://arxiv.org/abs/2203.13112) *— 2022 · arXiv:2203.13112*
54. [Benchmarking Machine Reading Comprehension: A Psychological Perspective](https://aclanthology.org/2021.eacl-main.137/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
55. [Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning](https://aclanthology.org/2021.emnlp-main.162/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
56. [COINS: Dynamically Generating COntextualized Inference Rules for Narrative Story Completion](https://aclanthology.org/2021.acl-long.395/) *— 2021 · 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)*
57. [COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences](https://aclanthology.org/2021.findings-acl.78/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
58. [Can Machines Learn Morality? The Delphi Experiment](https://arxiv.org/abs/2110.07574) *— 2021 · arXiv:2110.07574*
59. [Comparing Test Sets with Item Response Theory](https://aclanthology.org/2021.acl-long.92/) *— 2021 · 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)*
60. [CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://arxiv.org/abs/2104.08835) *— 2021 · arXiv:2104.08835*
61. [Do Natural Language Explanations Represent Valid Logical Arguments? Verifying Entailment in Explainable NLI Gold Standards](https://aclanthology.org/2021.iwcs-1.8/) *— 2021 · Proceedings of the 14th International Conference on Computational Semantics (IWCS)*
62. [Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings](https://aclanthology.org/2021.blackboxnlp-1.3/) *— 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP*
63. [Embracing Ambiguity: Shifting the Training Target of NLI Models](https://aclanthology.org/2021.acl-short.109/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
64. [ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning](https://arxiv.org/abs/2111.10952) *— 2021 · arXiv:2111.10952*
65. [ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning](https://aclanthology.org/2021.emnlp-main.609/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
66. [Explanations for CommonsenseQA: New Dataset and Models](https://aclanthology.org/2021.acl-long.238/) *— 2021 · 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)*
67. [Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Models](https://aclanthology.org/2021.emnlp-main.445/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
68. [Generating Hypothetical Events for Abductive Inference](https://aclanthology.org/2021.starsem-1.6/) *— 2021 · Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics*
69. [Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Tasks](https://aclanthology.org/2021.eacl-main.192/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
70. [Implicit Premise Generation with Discourse-aware Commonsense Knowledge Models](https://aclanthology.org/2021.emnlp-main.504/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
71. [Improving Unsupervised Commonsense Reasoning Using Knowledge-Enabled Natural Language Inference](https://aclanthology.org/2021.findings-emnlp.420/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
72. [Learning Event Graph Knowledge for Abductive Reasoning](https://aclanthology.org/2021.acl-long.403/) *— 2021 · 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)*
73. [Learning with Different Amounts of Annotation: From Zero to Many Labels](https://aclanthology.org/2021.emnlp-main.601/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
74. [MetaICL: Learning to Learn In Context](https://arxiv.org/abs/2110.15943) *— 2021 · arXiv:2110.15943*
75. [Modeling Event Plausibility with Consistent Conceptual Abstraction](https://aclanthology.org/2021.naacl-main.138/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
76. [Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences](https://aclanthology.org/2021.emnlp-main.54/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
77. [OTTers: One-turn Topic Transitions for Open-Domain Dialogue](https://aclanthology.org/2021.acl-long.194/) *— 2021 · 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)*
78. [On-the-Fly Attention Modulation for Neural Generation](https://aclanthology.org/2021.findings-acl.107/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
79. [Probing Across Time: What Does RoBERTa Know and When?](https://aclanthology.org/2021.findings-emnlp.71/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
80. [ProofWriter: Generating Implications, Proofs, and Abductive Statements over Natural Language](https://aclanthology.org/2021.findings-acl.317/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
81. [Reflective Decoding: Beyond Unidirectional Generation with Off-the-Shelf Language Models](https://aclanthology.org/2021.acl-long.114/) *— 2021 · 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)*
82. [RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge](https://aclanthology.org/2021.findings-acl.131/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
83. [TGEA: An Error-Annotated Dataset and Benchmark Tasks for TextGeneration from Pretrained Language Models](https://aclanthology.org/2021.acl-long.469/) *— 2021 · 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)*
84. [TellMeWhy: A Dataset for Answering Why-Questions in Narratives](https://md.mova.elamur.ai/free/en/docs/papers/lal-2021-tellmewhy-dataset-answering-why-questions/) *— our card · 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
85. [Temporal Reasoning on Implicit Events from Distant Supervision](https://aclanthology.org/2021.naacl-main.107/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
86. [Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understanding](https://aclanthology.org/2021.findings-emnlp.422/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
87. [UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark](https://arxiv.org/abs/2103.13009) *— 2021 · arXiv:2103.13009*
88. [What to Pre-Train on? Efficient Intermediate Task Selection](https://aclanthology.org/2021.emnlp-main.827/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
89. [Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution](https://aclanthology.org/2021.emnlp-main.670/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
90. [``I''m Not Mad'''': Commonsense Implications of Negation and Contradiction](https://aclanthology.org/2021.naacl-main.346/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
91. [Adversarial Filters of Dataset Biases](https://arxiv.org/abs/2002.04108) *— 2020 · arXiv:2002.04108*
92. [Adversarial NLI: A New Benchmark for Natural Language Understanding](https://aclanthology.org/2020.acl-main.441/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
93. [Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition](https://md.mova.elamur.ai/free/en/docs/papers/jeretic-2020-are-natural-language-inference-models/) *— our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
94. [Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning](https://aclanthology.org/2020.emnlp-main.58/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
95. [CSKG: The CommonSense Knowledge Graph](https://arxiv.org/abs/2012.11490) *— 2020 · arXiv:2012.11490 (ESWC 2021 Resource Track)*
96. [Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering](https://aclanthology.org/2020.findings-emnlp.369/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
97. [Continual Lifelong Learning in Natural Language Processing: A Survey](https://aclanthology.org/2020.coling-main.574/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
98. [Do We Need to Create Big Datasets to Learn a Task?](https://aclanthology.org/2020.sustainlp-1.23/) *— 2020 · Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing*
99. [INFOTABS: Inference on Tables as Semi-structured Data](https://aclanthology.org/2020.acl-main.210/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
100. [INSET: Sentence Infilling with INter-SEntential Transformer](https://aclanthology.org/2020.acl-main.226/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*

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