---
title: "Who cites Adam Pearce — 282 papers of our library"
description: "282 papers of the Elamur Research library cite the works of Adam Pearce, found in their bibliographies; the most cited first."
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---
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# Who cites Adam Pearce

283 citations of their works from 282 papers of our library (of the 149,439 whose bibliographies we read) · 48 with a page here, the most cited first · [← Adam Pearce](https://md.research.elamur.ai/free/en/authors/adam-pearce/)

1. [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
2. **[Quantifying Attention Flow in Transformers](https://md.research.elamur.ai/free/en/papers/abnar-2020-quantifying-attention-flow-transformers/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Samira Abnar, Willem Zuidema*2020 · 1,064 citations*
3. **[Integrating Multimodal Information in Large Pretrained Transformers](https://md.research.elamur.ai/free/en/papers/rahman-2020-integrating-multimodal-information-large-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wasifur Rahman, Md Kamrul Hasan, Sangwu Lee, et al.*2020 · 746 citations*
4. **[oLMpics — On what Language Model Pre-training Captures](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.*2019 · 440 citations*
5. **[Probing Pretrained Language Models for Lexical Semantics](https://md.research.elamur.ai/free/en/papers/vulic-2020-probing-pretrained-language-models-lexical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, et al.*2020 · 320 citations*
6. **[Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?](https://md.research.elamur.ai/free/en/papers/pruksachatkun-2020-intermediate-task-transfer-learning-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yada Pruksachatkun, Jason Phang, Haokun Liu, et al.*2020 · 281 citations*
7. **[Attention is Not Only a Weight: Analyzing Transformers with Vector Norms](https://md.research.elamur.ai/free/en/papers/kobayashi-2020-attention-is-not-only-weight/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi, et al.*2020 · 270 citations*
8. **[Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders](https://md.research.elamur.ai/free/en/papers/blevins-2020-moving-down-long-tail-word/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Terra Blevins, Luke Zettlemoyer*2020 · 232 citations*
9. **[What Happens To BERT Embeddings During Fine-tuning?](https://md.research.elamur.ai/free/en/papers/merchant-2020-what-happens-bert-embeddings-during/) [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/blackboxnlp/)**Amil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, et al.*2020 · 220 citations*
10. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining arXiv:2102.08473**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 198 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
11. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
12. **[The Linear Representation Hypothesis and the Geometry of Large Language Models](https://md.research.elamur.ai/free/en/papers/park-2023-linear-representation-hypothesis-geometry-large/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Kiho Park, Yo Joong Choe, Victor Veitch*2023 · 165 citations*
13. **[All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality](https://md.research.elamur.ai/free/en/papers/timkey-2021-all-bark-no-bite-rogue/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**William Timkey, Marten van Schijndel*2021 · 139 citations*
14. [**Function Vectors in Large Language Models arXiv:2310.15213**Eric Todd, Millicent L. Li, Arnab Sen Sharma, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/todd-2023-function-vectors-large-language-models/)
15. [**Finding Neurons in a Haystack: Case Studies with Sparse Probing arXiv:2305.01610**Wes Gurnee, Neel Nanda, Matthew Pauly, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gurnee-2023-finding-neurons-haystack-case-studies/)
16. **[Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color](https://md.research.elamur.ai/free/en/papers/abdou-2021-can-language-models-encode-perceptual/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Mostafa Abdou, Artur Kulmizev, Daniel Hershcovich, et al.*2021 · 122 citations*
17. **[On the Ability and Limitations of Transformers to Recognize Formal Languages](https://md.research.elamur.ai/free/en/papers/bhattamishra-2020-ability-limitations-transformers-recognize-formal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Satwik Bhattamishra, Kabir Ahuja, Navin Goyal*2020 · 113 citations*
18. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/)
19. [**Reasoning Models Don't Always Say What They Think arXiv:2505.05410**Yanda Chen, Joe Benton, Ansh Radhakrishnan, et al.*2025 · 106 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-reasoning-models-don-t-always/)
20. [**Are Transformers universal approximators of sequence-to-sequence functions? arXiv:1912.10077**Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, et al.*2019 · 97 citations*](https://md.research.elamur.ai/free/en/papers/yun-2019-transformers-universal-approximators-sequence-sequence/)
21. **[Interpretability at Scale: Identifying Causal Mechanisms in Alpaca](https://md.research.elamur.ai/free/en/papers/wu-2023-interpretability-scale-identifying-causal-mechanisms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhengxuan Wu, Atticus Geiger, Thomas Icard, et al.*2023 · 81 citations*
22. **[Let's Play Mono-Poly: BERT Can Reveal Words' Polysemy Level and Partitionability into Senses](https://md.research.elamur.ai/free/en/papers/soler-2021-let-s-play-mono-poly/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aina Garí Soler, Marianna Apidianaki*2021 · 75 citations*
23. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/)
24. **[Characterizing English Variation across Social Media Communities with BERT](https://md.research.elamur.ai/free/en/papers/lucy-2021-characterizing-english-variation-across-social/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Li Lucy, David Bamman*2021 · 57 citations*
25. **[Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries](https://md.research.elamur.ai/free/en/papers/biran-2024-hopping-too-late-exploring-limitations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eden Biran, Daniela Gottesman, Sohee Yang, et al.*2024 · 55 citations*
26. **[On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT](https://md.research.elamur.ai/free/en/papers/ravichander-2020-systematicity-probing-contextualized-word-representations/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Abhilasha Ravichander, Eduard Hovy, Kaheer Suleman, et al.*2020 · 55 citations*
27. **[Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers](https://md.research.elamur.ai/free/en/papers/dumas-2025-separating-tongue-thought-activation-patching/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Clément Dumas, Chris Wendler, Veniamin Veselovsky, et al.*2025 · 27 citations*
28. **[Construction Grammar Provides Unique Insight into Neural Language Models](https://md.research.elamur.ai/free/en/papers/weissweiler-2023-construction-grammar-provides-unique-insight/) [International Workshop on Construction Grammars and NLP](https://md.research.elamur.ai/free/en/venues/cxgsnlp/)**Leonie Weissweiler, Taiqi He, Naoki Otani, et al.*2023 · 26 citations*
29. **[Morphosyntactic probing of multilingual BERT models](https://md.research.elamur.ai/free/en/papers/acs-2023-morphosyntactic-probing-multilingual-bert-models/) [Natural Language Engineering](https://md.research.elamur.ai/free/en/venues/natural-language-engineering/)**Judit Acs, Endre Hamerlik, Roy Schwartz, et al.*2023 · 26 citations*
30. **[Lexical Semantics with Large Language Models: A Case Study of English “break”](https://md.research.elamur.ai/free/en/papers/petersen-2023-lexical-semantics-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Erika Petersen, Christopher Potts*2023 · 17 citations*
31. **[Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race](https://md.research.elamur.ai/free/en/papers/sun-2025-aligned-but-blind-alignment-increases/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lihao Sun, Chengzhi Mao, Valentin Hofmann, et al.*2025 · 10 citations*
32. **[How Fast can BERT Learn Simple Natural Language Inference?](https://md.research.elamur.ai/free/en/papers/lin-2021-how-fast-can-bert-learn/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yi-Chung Lin, Keh-Yih Su*2021 · 10 citations*
33. **[Paths Not Taken: Understanding and Mending the Multilingual Factual Recall Pipeline](https://md.research.elamur.ai/free/en/papers/lu-2025-paths-not-taken-understanding-mending/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Meng Lu, Ruochen Zhang, Carsten Eickhoff, et al.*2025 · 9 citations*
34. **[Pixels Versus Priors: Controlling Knowledge Priors in Vision-Language Models through Visual Counterfacts](https://md.research.elamur.ai/free/en/papers/golovanevsky-2025-pixels-versus-priors-controlling-knowledge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Michal Golovanevsky, William Rudman, Michael A. Lepori, et al.*2025 · 8 citations*
35. **[Localized Cultural Knowledge is Conserved and Controllable in Large Language Models](https://md.research.elamur.ai/free/en/papers/veselovsky-2026-localized-cultural-knowledge-is-conserved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Veniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.*2026 · 7 citations*
36. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
37. [**Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models arXiv:2605.11887**Boyi Deng, Xu Wang, Yaoning Wang, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deng-2026-qwen-scope-turning-sparse/)
38. [**Modeling the Evolution of English Noun Compounds with Feature-Rich Diachronic Compositionality Prediction**Filip Miletić, Sabine Schulte im Walde*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/miletic-2025-modeling-evolution-english-noun-compounds/)
39. **[In-Context Representation Hijacking](https://md.research.elamur.ai/free/en/papers/yona-2026-context-representation-hijacking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Itay Yona, Amir Sarid, Michael Karasik, et al.*2026 · 2 citations*
40. **[Rhetorical Questions in LLM Representations: A Linear Probing Study](https://md.research.elamur.ai/free/en/papers/yao-2026-rhetorical-questions-llm-representations-linear/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Louie Hong Yao, Vishesh Anand, Yuan Zhuang, et al.*2026 · 1 citation*
41. **[Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://md.research.elamur.ai/free/en/papers/reif-2026-vocab-diet-reshaping-vocabulary-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuval Reif, Guy Kaplan, Roy Schwartz*2026 · 1 citation*
42. **[A framework for analyzing concept representations in neural models](https://md.research.elamur.ai/free/en/papers/naowarat-2026-framework-analyzing-concept-representations-neural/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Burin Naowarat, Hao Tang, Sharon Goldwater*2026*
43. **[Beyond Prompt: Fine-grained Simulation of Cognitively Impaired Standardized Patients via Stochastic Steering](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-prompt-fine-grained-simulation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weikang Zhang, Zimo Zhu, Zhichuan Yang, et al.*2026*
44. **[Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework](https://md.research.elamur.ai/free/en/papers/zhang-2026-less-languages-less-tokens-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenyuan Zhang, Qiguang Chen, Xie Chen, et al.*2026*
45. **[Mechanistic Insights into Deferred Semantic Drift in LLMs](https://md.research.elamur.ai/free/en/papers/zeng-2026-mechanistic-insights-into-deferred-semantic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingjie Zeng, Huayang Li, Liang Yang, et al.*2026*
46. **[ReFreeKV: Towards Threshold-Free KV Cache Compression](https://md.research.elamur.ai/free/en/papers/ni-2026-refreekv-threshold-free-kv-cache/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanfan Ni, Liyan Xu, Chenyang Lyu, et al.*2026*
47. **[The Illusion of Specialization: Unveiling the Domain-Invariant “Standing Committee” in Mixture-of-Experts Models](https://md.research.elamur.ai/free/en/papers/wang-2026-illusion-specialization-unveiling-domain-invariant/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yan Wang, Yitao Xu, Nanhan Shen, et al.*2026*
48. **[Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations](https://md.research.elamur.ai/free/en/papers/luo-2026-two-pathways-truthfulness-intrinsic-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Luo, Guangyue Peng, Wei Li, et al.*2026*

234 more citing papers of our library have no page here yet.

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