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# Who cites «Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference»

699 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/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/)

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1. [1,729 vs. 1729: The Effect of Scripts and Formats on LLM Numeracy](https://aclanthology.org/2026.findings-acl.518/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
2. [Annotation Entropy Predicts Per-Example Learning Dynamics in LoRA Fine-Tuning](https://aclanthology.org/2026.acl-srw.11/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
3. [Chinese Live-Streaming E-Commerce Morph Resolution: Datasets and Methods](https://aclanthology.org/2026.findings-acl.126/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
4. [Compositional Meaning Representations in LLMs: a Critical Review of Probing Studies](https://aclanthology.org/2026.starsem-conference.13/) *— 2026 · Proceedings of the 15th Joint Conference on Lexical and Computational Semantics (*SEM 2026)*
5. [CxMP: A Linguistic Minimal-Pair Benchmark for Evaluating Constructional Understanding in Language Models](https://aclanthology.org/2026.acl-long.2132/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
6. [Dataset Cartography for Implicit Discourse Relation Recognition: Promises and Pitfalls](https://aclanthology.org/2026.codi-1.8/) *— 2026 · Proceedings of the 2nd Joint Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences and Computational Models of Reference, Anaphora and Coreference (CODI-CRAC 2026)*
7. [Debiasing Reward Models via Causally Motivated Inference-Time Intervention](https://aclanthology.org/2026.acl-long.1029/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
8. [Different types of syntactic agreement recruit the same units within large language models](https://aclanthology.org/2026.acl-long.7/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
9. [Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation](https://aclanthology.org/2026.lrec-1.549/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
10. [FLUKE: A Linguistically-Driven and Task-Agnostic Framework for Robustness Evaluation](https://aclanthology.org/2026.findings-eacl.269/) *— 2026 · Findings of the Association for Computational Linguistics: EACL 2026*
11. [Faithful Autoformalization via Roundtrip Verification and Repair](https://arxiv.org/abs/2604.25031) *— 2026 · arXiv:2604.25031*
12. [HABIB_TAZ at SemEval-2026 Task 11: Disentangling Formal Logic from Content via Synthetic Training and Multi-Objective Optimization](https://aclanthology.org/2026.semeval-1.139/) *— 2026 · Proceedings of the 20th International Workshop on Semantic Evaluation (2026)*
13. [Identifying the Achilles'' Heel: An Iterative Method for Uncovering Factual Errors in Large Language Models](https://aclanthology.org/2026.findings-acl.1714/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
14. [Large Language Models Are Still Misled by Simple Bias Ensembles](https://aclanthology.org/2026.findings-acl.971/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
15. [Measuring and Mitigating Shortcut Reliance in Language Models with Probe-Based Representation Entanglement](https://aclanthology.org/2026.acl-srw.59/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
16. [Moneyball with LLMs: Analyzing Tabular Summarization in Sports Narratives](https://aclanthology.org/2026.findings-acl.2072/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
17. [Multi-Legal-Bench: When the Answer Is in the Input. Label Leakage in Legal Benchmarks Built from Court Registries](https://arxiv.org/abs/2605.29738) *— 2026 · arXiv:2605.29738*
18. [Out-Of-Tune rather than Fine-Tuned: How Pre-training, Fine-tuning and Tokenization Affect Semantic Similarity in a Historical, Non-Standardized Domain](https://aclanthology.org/2026.loreslm-1.45/) *— 2026 · Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)*
19. [Position: Correct Answer, Wrong Mechanism -- When AI Scientists Defend General Claims Their Own Data Contradicts](https://arxiv.org/abs/2606.23175) *— 2026 · arXiv:2606.23175*
20. [Privacy Washing: Detecting Internal Contradictions in Privacy Policies](https://arxiv.org/abs/2609.02055) *— 2026 · arXiv:2609.02055*
21. [Qomhrá: A Bilingual Irish and English Large Language Model](https://aclanthology.org/2026.loreslm-1.18/) *— 2026 · Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)*
22. [Shortcut Learning in Legal Judgment Prediction: Empirical Evidence from the UK Employment Tribunal](https://arxiv.org/abs/2607.04261) *— 2026 · arXiv:2607.04261*
23. [Stylistic Evolution and LLM Neutrality in Singlish Language](https://arxiv.org/abs/2601.06580) *— 2026 · arXiv:2601.06580*
24. [The Imperfective Paradox in Large Language Models](https://aclanthology.org/2026.acl-long.689/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
25. [The Validity of Coreference-based Evaluations of Natural Language Understanding](https://arxiv.org/abs/2602.16200) *— 2026 · arXiv:2602.16200*
26. [There Is No Spoon: Existential Presupposition in Large Language Models](https://aclanthology.org/2026.lrec-1.161/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
27. [Toward Cognitive Alignment in Large Language Models: Integrating Linguistic Theory and Human Data](https://aclanthology.org/2026.cmcl-1.26/) *— 2026 · Proceedings of the 15th Workshop on Cognitive Modeling and Computational Linguistics*
28. [An Empirical Analysis of Machine Translation for Expanding Multilingual Benchmarks](https://aclanthology.org/2025.wmt-1.1/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
29. [Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases](https://aclanthology.org/2025.acl-long.478/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
30. [Characterizing the Role of Similarity in the Property Inferences of Language Models](https://aclanthology.org/2025.naacl-long.574/) *— 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)*
31. [Construction Identification and Disambiguation Using BERT: A Case Study of NPN](https://aclanthology.org/2025.conll-1.24/) *— 2025 · Proceedings of the 29th Conference on Computational Natural Language Learning*
32. [Constructions are Revealed in Word Distributions](https://aclanthology.org/2025.emnlp-main.108/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
33. [Elements of World Knowledge ( EWoK ): A Cognition-Inspired Framework for Evaluating Basic World Knowledge in Language Models](https://aclanthology.org/2025.tacl-1.57/) *— 2025*
34. [Evaluating Syntactic Generalization in Transformer-Based Models Using Korean Honorific Agreement](https://aclanthology.org/2025.paclic-1.3/) *— 2025 · Proceedings of the 39th Pacific Asia Conference on Language, Information and Computation*
35. [LingGym: How Far Are LLMs from Thinking Like Field Linguists?](https://aclanthology.org/2025.emnlp-main.69/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
36. [Linguistic Generalizations are not Rules: Impacts on Evaluation of LMs](https://aclanthology.org/2025.cxgsnlp-1.7/) *— 2025 · Proceedings of the Second International Workshop on Construction Grammars and NLP*
37. [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)*
38. [NeoQA: Evidence-based Question Answering with Generated News Events](https://aclanthology.org/2025.findings-acl.616/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
39. [On Reference (In-)Determinacy in Natural Language Inference](https://aclanthology.org/2025.findings-naacl.450/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
40. [On Tables with Numbers, with Numbers](https://aclanthology.org/2025.lm4uc-1.12/) *— 2025 · Proceedings of the 1st Workshop on Language Models for Underserved Communities (LM4UC 2025)*
41. [Sneaking Syntax into Transformer Language Models with Tree Regularization](https://aclanthology.org/2025.naacl-long.407/) *— 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)*
42. [Temporal Relation Classification: An XAI Perspective](https://aclanthology.org/2025.nodalida-1.72/) *— 2025 · Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)*
43. [Understanding Figurative Meaning through Explainable Visual Entailment](https://aclanthology.org/2025.naacl-long.1/) *— 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)*
44. [When Does Meaning Backfire? Investigating the Role of AMRs in NLI](https://aclanthology.org/2025.starsem-1.16/) *— 2025 · Proceedings of the 14th Joint Conference on Lexical and Computational Semantics (*SEM 2025)*
45. [reWordBench: Benchmarking and Improving the Robustness of Reward Models with Transformed Inputs](https://aclanthology.org/2025.emnlp-main.167/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
46. [A Primer on the Inner Workings of Transformer-based Language Models](https://arxiv.org/abs/2405.00208) *— 2024 · arXiv:2405.00208*
47. [ALVIN: Active Learning Via INterpolation](https://aclanthology.org/2024.emnlp-main.1265/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
48. [AMREx: AMR for Explainable Fact Verification](https://aclanthology.org/2024.fever-1.26/) *— 2024 · Proceedings of the Seventh Fact Extraction and VERification Workshop (FEVER)*
49. [APPLS: Evaluating Evaluation Metrics for Plain Language Summarization](https://aclanthology.org/2024.emnlp-main.519/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
50. [Analyzing the Evaluation of Cross-Lingual Knowledge Transfer in Multilingual Language Models](https://aclanthology.org/2024.eacl-long.177/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
51. [Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs](https://aclanthology.org/2024.tacl-1.60/) *— 2024 · Transactions of the Association for Computational Linguistics*
52. [Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification](https://aclanthology.org/2024.findings-acl.618/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
53. [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)*
54. [Benchmark Transparency: Measuring the Impact of Data on Evaluation](https://aclanthology.org/2024.naacl-long.86/) *— 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. [Best of Both Worlds: A Pliable and Generalizable Neuro-Symbolic Approach for Relation Classification](https://aclanthology.org/2024.findings-naacl.165/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
56. [Beyond Agreement: Diagnosing the Rationale Alignment of Automated Essay Scoring Methods based on Linguistically-informed Counterfactuals](https://aclanthology.org/2024.findings-emnlp.520/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
57. [CHARP: Conversation History AwaReness Probing for Knowledge-grounded Dialogue Systems](https://aclanthology.org/2024.findings-acl.90/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
58. [Causal-Guided Active Learning for Debiasing Large Language Models](https://aclanthology.org/2024.acl-long.778/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
59. [Cheetah: Natural Language Generation for 517 African Languages](https://aclanthology.org/2024.acl-long.691/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
60. [ConSiDERS-The-Human Evaluation Framework: Rethinking Human Evaluation for Generative Large Language Models](https://aclanthology.org/2024.acl-long.63/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
61. [Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasons](https://aclanthology.org/2024.lrec-main.336/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
62. [Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models](https://aclanthology.org/2024.emnlp-main.679/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
63. [Experimental Contexts Can Facilitate Robust Semantic Property Inference in Language Models, but Inconsistently](https://aclanthology.org/2024.emnlp-main.687/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
64. [Explore Spurious Correlations at the Concept Level in Language Models for Text Classification](https://aclanthology.org/2024.acl-long.28/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
65. [Exploring Continual Learning of Compositional Generalization in NLI](https://aclanthology.org/2024.tacl-1.51/) *— 2024 · Transactions of the Association for Computational Linguistics*
66. [Exploring and Mitigating Shortcut Learning for Generative Large Language Models](https://aclanthology.org/2024.lrec-main.602/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
67. [Extending the BabyLM Initiative : Promoting Diversity in Datasets and Metrics through High-Quality Linguistic Corpora](https://aclanthology.org/2024.conll-babylm.12/) *— 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning*
68. [FairFlow: Mitigating Dataset Biases through Undecided Learning for Natural Language Understanding](https://aclanthology.org/2024.emnlp-main.1225/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
69. [Filtered Corpus Training (FiCT) Shows that Language Models Can Generalize from Indirect Evidence](https://aclanthology.org/2024.tacl-1.87/) *— 2024 · Transactions of the Association for Computational Linguistics*
70. [Fuse to Forget: Bias Reduction and Selective Memorization through Model Fusion](https://aclanthology.org/2024.emnlp-main.1045/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
71. [Groundedness in Retrieval-augmented Long-form Generation: An Empirical Study](https://aclanthology.org/2024.findings-naacl.100/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
72. [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*
73. [How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field Study](https://aclanthology.org/2024.acl-long.795/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
74. [ICLEF: In-Context Learning with Expert Feedback for Explainable Style Transfer](https://aclanthology.org/2024.acl-long.854/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
75. [In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax](https://aclanthology.org/2024.naacl-long.267/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
76. [It is not True that Transformers are Inductive Learners: Probing NLI Models with External Negation](https://aclanthology.org/2024.eacl-long.116/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
77. [LLMs Are Prone to Fallacies in Causal Inference](https://aclanthology.org/2024.emnlp-main.590/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
78. [Large Language Models are not Fair Evaluators](https://aclanthology.org/2024.acl-long.511/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
79. [Linguistic Rule Induction Improves Adversarial and OOD Robustness in Large Language Models](https://aclanthology.org/2024.lrec-main.924/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
80. [LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models](https://aclanthology.org/2024.acl-long.739/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
81. [Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals](https://aclanthology.org/2024.findings-emnlp.205/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
82. [Measuring the Robustness of NLP Models to Domain Shifts](https://aclanthology.org/2024.findings-emnlp.7/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
83. [Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation](https://aclanthology.org/2024.emnlp-main.347/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
84. [MultiPragEval: Multilingual Pragmatic Evaluation of Large Language Models](https://aclanthology.org/2024.genbench-1.7/) *— 2024 · Proceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLP*
85. [Natural Language Satisfiability: Exploring the Problem Distribution and Evaluating Transformer-based Language Models](https://aclanthology.org/2024.acl-long.815/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
86. [Navigating the Shortcut Maze: A Comprehensive Analysis of Shortcut Learning in Text Classification by Language Models](https://aclanthology.org/2024.findings-emnlp.146/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
87. [No Context Needed: Contextual Quandary In Idiomatic Reasoning With Pre-Trained Language Models](https://aclanthology.org/2024.naacl-long.272/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
88. [Not Eliminate but Aggregate: Post-Hoc Control over Mixture-of-Experts to Address Shortcut Shifts in Natural Language Understanding](https://aclanthology.org/2024.tacl-1.70/) *— 2024 · Transactions of the Association for Computational Linguistics*
89. [On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?](https://arxiv.org/abs/2406.14267) *— 2024 · arXiv:2406.14267*
90. [PairCFR: Enhancing Model Training on Paired Counterfactually Augmented Data through Contrastive Learning](https://aclanthology.org/2024.acl-long.646/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
91. [Pragmatic Norms Are All You Need – Why The Symbol Grounding Problem Does Not Apply to LLMs](https://aclanthology.org/2024.emnlp-main.651/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
92. [Principles from Clinical Research for NLP Model Generalization](https://aclanthology.org/2024.naacl-long.127/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
93. [RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting](https://arxiv.org/abs/2412.07675) *— 2024 · arXiv:2412.07675*
94. [Revealing the Parametric Knowledge of Language Models: A Unified Framework for Attribution Methods](https://aclanthology.org/2024.acl-long.444/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
95. [Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI Models](https://aclanthology.org/2024.eacl-long.27/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
96. [Solving the Challenge Set without Solving the Task: On Winograd Schemas as a Test of Pronominal Coreference Resolution](https://aclanthology.org/2024.conll-1.38/) *— 2024 · Proceedings of the 28th Conference on Computational Natural Language Learning*
97. [The Heuristic Core: Understanding Subnetwork Generalization in Pretrained Language Models](https://aclanthology.org/2024.acl-long.774/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
98. [Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection](https://aclanthology.org/2024.findings-emnlp.693/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
99. [Think Twice: Measuring the Efficiency of Eliminating Prediction Shortcuts of Question Answering Models](https://aclanthology.org/2024.eacl-long.133/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
100. [Toward Compositional Behavior in Neural Models: A Survey of Current Views](https://aclanthology.org/2024.emnlp-main.524/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*

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