Who cites «Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation»

68 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

1. Multi-component Causal Tracing in Large Language Models — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
2. The Validity of Coreference-based Evaluations of Natural Language Understanding — 2026 · arXiv:2602.16200
3. Thunder-NUBench: A Benchmark for LLMs'' Sentence-Level Negation Understanding — 2026 · Findings of the Association for Computational Linguistics: EACL 2026
4. When Models Decide and When They Bind: A Two-Stage Computation for Multiple-Choice Question Answering — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
5. Characterizing the Role of Similarity in the Property Inferences of Language Models — 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)
6. Sneaking Syntax into Transformer Language Models with Tree Regularization — 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)
7. Steering off Course: Reliability Challenges in Steering Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
8. A Primer on the Inner Workings of Transformer-based Language Models — 2024 · arXiv:2405.00208
9. AtP*: An efficient and scalable method for localizing LLM behaviour to components — 2024 · arXiv:2403.00745
10. Exploring Continual Learning of Compositional Generalization in NLI — 2024 · Transactions of the Association for Computational Linguistics
11. Information Flow Routes: Automatically Interpreting Language Models at Scale — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
12. LM Transparency Tool: Interactive Tool for Analyzing Transformer Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
13. Language Models Linearly Represent Sentiment — 2024 · Proceedings of the 7th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP
14. Mission: Impossible Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
15. RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
16. Recurrent Neural Networks Learn to Store and Generate Sequences using Non-Linear Representations — 2024 · Proceedings of the 7th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP
17. Representational Analysis of Binding in Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
18. Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI Models — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
19. Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
20. COMPS: Conceptual Minimal Pair Sentences for testing Robust Property Knowledge and its Inheritance in Pre-trained Language Models — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
21. Causal Abstraction for Chain-of-Thought Reasoning in Arithmetic Word Problems — 2023 · Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP
22. Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability — 2023 · arXiv:2301.04709
23. Causal interventions expose implicit situation models for commonsense language understanding — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
24. Interpretability at Scale: Identifying Causal Mechanisms in Alpaca — 2023 · arXiv:2305.08809
25. Interventional Probing in High Dimensions: An NLI Case Study — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
26. Language models are not naysayers: An analysis of language models on negation benchmarks — 2023 · arXiv:2306.08189
27. Linear Representations of Sentiment in Large Language Models — 2023 · arXiv:2310.15154
28. Localizing Model Behavior with Path Patching — 2023 · arXiv:2304.05969
29. SETI: Systematicity Evaluation of Textual Inference — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
30. ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
31. The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets — 2023 · arXiv:2310.06824
32. Towards Best Practices of Activation Patching in Language Models: Metrics and Methods — 2023 · arXiv:2309.16042
33. ANLIzing the Adversarial Natural Language Inference Dataset — 2022 · Proceedings of the Society for Computation in Linguistics 2022
34. An Analysis of Negation in Natural Language Understanding Corpora — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
35. CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
36. Can Transformers Reason in Fragments of Natural Language? — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
37. Causal Distillation for Language Models — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
38. Decomposing Natural Logic Inferences for Neural NLI — 2022 · Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
39. It Is Not Easy To Detect Paraphrases: Analysing Semantic Similarity With Antonyms and Negation Using the New SemAntoNeg Benchmark — 2022 · Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
40. Neuro-symbolic Natural Logic with Introspective Revision for Natural Language Inference — 2022 · Transactions of the Association for Computational Linguistics
41. Simple but Challenging: Natural Language Inference Models Fail on Simple Sentences — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
42. A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs — 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
43. Causal Abstractions of Neural Networks — 2021 · arXiv:2106.02997
44. Constructing Taxonomies from Pretrained Language Models — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
45. Exploring Transitivity in Neural NLI Models through Veridicality — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
46. Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
47. Issues with Entailment-based Zero-shot Text Classification — 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)
48. Modeling Event Plausibility with Consistent Conceptual Abstraction — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
49. Supporting Context Monotonicity Abstractions in Neural NLI Models — 2021 · Proceedings of the 1st and 2nd Workshops on Natural Logic Meets Machine Learning (NALOMA)
50. SyGNS: A Systematic Generalization Testbed Based on Natural Language Semantics — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
51. bylinina-2022-transformers-loop-polarity-neural-models
52. canby-2025-how-reliable-are-causal-probing
53. dai-2026-cell-based-representation-relational-binding
54. dutt-2024-investigating-generalizability-pretrained-language-models
55. feucht-2026-arithmetic-wild-llama-uses-base
56. fu-2024-compositional-structured-explanation-generation-dynamic
57. jabbar-2025-distinguishing-fair-unfair-compositional-generalization
58. jiang-2026-immediate-inference-missing-foundation-large
59. junias-2026-logical-commonsenseqa-benchmark-logical-commonsense
60. larraya-2026-assessing-logical-coherence-llms-fine
61. mircea-2023-balaur-language-model-pretraining-lexical
62. rozanova-2024-estimating-causal-effects-natural-logic
63. saphra-2024-mechanistic
64. sineva-2021-negation-instance-based-evaluation-end
65. tao-2024-inference-verbalization-functions-during-context
66. wu-2022-identifying-limits-cross-domain-knowledge
67. wu-2024-textttpyvene-library-understanding-improving-pytorch
68. zheng-2023-natlogattack-framework-attacking-natural-language

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