---
title: "Who cites Tamera Lanham — page 2 — 687 papers of our library"
description: "687 papers of the Elamur Research library cite the works of Tamera Lanham, found in their bibliographies · page 2 of 3 · 101–200; the most…"
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---
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# Who cites Tamera Lanham

778 citations of their works from 687 papers of our library (of the 149,439 whose bibliographies we read) · 237 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Tamera Lanham](https://md.research.elamur.ai/free/en/authors/tamera-lanham/)

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101. [**The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation arXiv:2312.09085**Rongwu Xu, Brian S. Lin, Shujian Yang, et al.*2023 · 56 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-earth-flat-because-investigating-llms/)
102. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
103. [**Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs arXiv:2402.14903**Aaditya K. Singh, DJ Strouse*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-tokenization-counts-impact-tokenization-arithmetic/)
104. [**In-context Learning with Retrieved Demonstrations for Language Models: A Survey arXiv:2401.11624**Man Luo, Xin Xu, Yue Liu, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-context-learning-retrieved-demonstrations-language/)
105. [**Chain-of-Thought Reasoning In The Wild Is Not Always Faithful arXiv:2503.08679**Ivan Arcuschin, Jett Janiak, Robert Krzyzanowski, et al.*2025 · 52 citations*](https://md.research.elamur.ai/free/en/papers/arcuschin-2025-chain-thought-reasoning-wild-always/)
106. [**Critique-out-Loud Reward Models arXiv:2408.11791**Zachary Ankner, Mansheej Paul, Brandon Cui, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/ankner-2024-critique-out-loud-reward-models/)
107. [**Explore, Establish, Exploit: Red Teaming Language Models from Scratch arXiv:2306.09442**Stephen Casper, Jason Lin, Joe Kwon, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/casper-2023-explore-establish-exploit-red-teaming/)
108. **[Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision](https://md.research.elamur.ai/free/en/papers/sun-2024-easy-hard-generalization-scalable-alignment/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhiqing Sun, Longhui Yu, Yikang Shen, et al.*2024 · 51 citations*
109. [**Formal Mathematical Reasoning: A New Frontier in AI arXiv:2412.16075**Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-formal-mathematical-reasoning-new-frontier/)
110. **[NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Models](https://md.research.elamur.ai/free/en/papers/rao-2025-normad-framework-measuring-cultural-adaptability/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Abhinav Rao, Akhila Yerukola, Vishwa Shah, et al.*2025 · 46 citations*
111. **[“According to . . . “: Prompting Language Models Improves Quoting from Pre-Training Data](https://md.research.elamur.ai/free/en/papers/weller-2024-according-prompting-language-models-improves/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Orion Weller, Marc Marone, Nathaniel Weir, et al.*2024 · 46 citations*
112. **[Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception](https://md.research.elamur.ai/free/en/papers/lin-2025-investigating-bias-llm-based-bias/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Luyang Lin, Lingzhi Wang, Jinsong Guo, et al.*2025 · 44 citations*
113. [**Thought Anchors: Which LLM Reasoning Steps Matter? arXiv:2506.19143**Paul C. Bogdan, Uzay Macar, Neel Nanda, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/bogdan-2025-thought-anchors-which-llm-reasoning/)
114. [**Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration arXiv:2310.00280**Qiushi Sun, Zhangyue Yin, Xiang Li, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-corex-pushing-boundaries-complex-reasoning/)
115. [**SALMON: Self-Alignment with Instructable Reward Models arXiv:2310.05910**Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-salmon-self-alignment-instructable-reward/)
116. [**DeepRAG: Thinking to Retrieve Step by Step for Large Language Models arXiv:2502.01142**Xinyan Guan, Jiali Zeng, Fandong Meng, et al.*2025 · 40 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-deeprag-thinking-retrieve-step-step/)
117. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
118. **[SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-sciinstruct-self-reflective-instruction-annotated/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Dan Zhang, Ziniu Hu, Sining Zhoubian, et al.*2024 · 37 citations*
119. [**Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing arXiv:2305.16635**Jaehun Jung, Peter West, Liwei Jiang, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/jung-2023-impossible-distillation-low-quality-model/)
120. **[Benchmarking Distributional Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/meister-2025-benchmarking-distributional-alignment-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto*2025 · 35 citations*
121. [**Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap arXiv:2402.19450**Saurabh Srivastava, Annarose M B, Anto P, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2024-functional-benchmarks-robust-evaluation-reasoning/)
122. **[PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning](https://md.research.elamur.ai/free/en/papers/zhu-2024-pad-program-aided-distillation-can/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xuekai Zhu, Biqing Qi, Kaiyan Zhang, et al.*2024 · 35 citations*
123. [**Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation arXiv:2306.05783**Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-xiezhi-ever-updating-benchmark/)
124. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
125. [**Interpretable Unified Language Checking arXiv:2304.03728**Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-interpretable-unified-language-checking/)
126. **[Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing](https://md.research.elamur.ai/free/en/papers/jiao-2024-learning-planning-based-reasoning-trajectories/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.*2024 · 31 citations*
127. [**Language Models as Science Tutors arXiv:2402.11111**Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/chevalier-2024-language-models-science-tutors/)
128. **[Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling](https://md.research.elamur.ai/free/en/papers/wan-2025-reasoning-aware-self-consistency-leveraging/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guangya Wan, Yuqi Wu, Jie Chen, et al.*2025 · 29 citations*
129. [**Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models arXiv:2310.00836**Man Luo, Shrinidhi Kumbhar, Ming shen, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-towards-logiglue-brief-survey-benchmark/)
130. [**Feedback Loops With Language Models Drive In-Context Reward Hacking arXiv:2402.06627**Alexander Pan, Erik Jones, Meena Jagadeesan, et al.*2024 · 26 citations*](https://md.research.elamur.ai/free/en/papers/pan-2024-feedback-loops-language-models-drive/)
131. **[Language Models in Dialogue: Conversational Maxims for Human-AI Interactions](https://md.research.elamur.ai/free/en/papers/miehling-2024-language-models-dialogue-conversational-maxims/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Erik Miehling, Manish Nagireddy, Prasanna Sattigeri, et al.*2024 · 23 citations*
132. **[Answer Convergence as a Signal for Early Stopping in Reasoning](https://md.research.elamur.ai/free/en/papers/liu-2025-answer-convergence-as-signal-early/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Liu, Lu Wang*2025 · 22 citations*
133. **[How Likely Do LLMs with CoT Mimic Human Reasoning?](https://md.research.elamur.ai/free/en/papers/bao-2025-how-likely-do-llms-cot/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Guangsheng Bao, Hongbo Zhang, Cunxiang Wang, et al.*2025 · 22 citations*
134. [**AI Sandbagging: Language Models can Strategically Underperform on Evaluations arXiv:2406.07358**Teun van der Weij, Felix Hofstatter, Ollie Jaffe, et al.*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/weij-2024-ai-sandbagging-language-models-strategically/)
135. **[Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens](https://md.research.elamur.ai/free/en/papers/zhao-2026-is-chain-thought-reasoning-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengshuai Zhao, Zhen Tan, Pingchuan Ma, et al.*2026 · 21 citations*
136. **[Intention Analysis Makes LLMs A Good Jailbreak Defender](https://md.research.elamur.ai/free/en/papers/zhang-2025-intention-analysis-makes-llms-good/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuqi Zhang, Liang Ding, Lefei Zhang, et al.*2025 · 21 citations*
137. [**Quality-Diversity through AI Feedback arXiv:2310.13032**Herbie Bradley, Andrew Dai, Hannah Teufel, et al.*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bradley-2023-quality-diversity-through-ai-feedback/)
138. **[Conformity in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2025-conformity-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaochen Zhu, Caiqi Zhang, Tom Stafford, et al.*2025 · 18 citations*
139. **[LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts](https://md.research.elamur.ai/free/en/papers/ren-2025-llms-know-their-vulnerabilities-uncover/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qibing Ren, Hao Li, Dongrui Liu, et al.*2025 · 18 citations*
140. [**ChatGLM-RLHF: Practices of Aligning Large Language Models with Human Feedback arXiv:2404.00934**Zhenyu Hou, Yilin Niu, Zhengxiao Du, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/hou-2024-chatglm-rlhf-practices-aligning/)
141. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
142. **[Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps](https://md.research.elamur.ai/free/en/papers/tutek-2025-measuring-chain-thought-faithfulness-unlearning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, et al.*2025 · 15 citations*
143. **[Evaluating Large Language Models for Health-related Queries with Presuppositions](https://md.research.elamur.ai/free/en/papers/kaur-2024-evaluating-large-language-models-health/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Navreet Kaur, Monojit Choudhury, Danish Pruthi*2024 · 15 citations*
144. **[Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms](https://md.research.elamur.ai/free/en/papers/wang-2025-beyond-prompt-engineering-robust-behavior/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ziwen Xu, Shengyu Mao, et al.*2025 · 14 citations*
145. [**Aligning Large Language Models with Human Opinions through Persona Selection and Value — Belief — Norm Reasoning arXiv:2311.08385**Do Xuan Long, Kenji Kawaguchi, Min-Yen Kan, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/long-2023-aligning-large-language-models-human/)
146. **[Do Large Language Models Mirror Cognitive Language Processing?](https://md.research.elamur.ai/free/en/papers/ren-2025-do-large-language-models-mirror/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuqi Ren, Renren Jin, Tongxuan Zhang, et al.*2025 · 11 citations*
147. **[Multiple LLM Agents Debate for Equitable Cultural Alignment](https://md.research.elamur.ai/free/en/papers/ki-2025-multiple-llm-agents-debate-equitable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dayeon Ki, Rachel Rudinger, Tianyi Zhou, et al.*2025 · 10 citations*
148. **[Stepwise Reasoning Disruption Attack of LLMs](https://md.research.elamur.ai/free/en/papers/peng-2025-stepwise-reasoning-disruption-attack-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Peng, Maolin Wang, Xiangyu Zhao, et al.*2025 · 10 citations*
149. [**Preventing Language Models From Hiding Their Reasoning arXiv:2310.18512**Fabien Roger, Ryan Greenblatt*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/roger-2023-preventing-language-models-hiding-their/)
150. **[FaithLM: Towards Faithful Explanations for Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2026-faithlm-faithful-explanations-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, et al.*2026 · 9 citations*
151. **[Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning](https://md.research.elamur.ai/free/en/papers/bi-2025-enhancing-reasoning-capabilities-small-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jing Bi, Yuting Wu, Weiwei Xing, et al.*2025 · 8 citations*
152. **[A Comprehensive Evaluation of Multilingual Chain-of-Thought Reasoning: Performance, Consistency, and Faithfulness Across Languages](https://md.research.elamur.ai/free/en/papers/zhao-2026-comprehensive-evaluation-multilingual-chain-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raoyuan Zhao, Yihong Liu, Hinrich Schuetze, et al.*2026 · 7 citations*
153. **[FACT-E: Causality-Inspired Evaluation for Trustworthy Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2026-fact-e-causality-inspired-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxi Sun, Aoqi Zuo, Haotian Xie, et al.*2026 · 7 citations*
154. [**Cancer-Myth: Evaluating Large Language Models on Patient Questions with False Presuppositions arXiv:2504.11373**Wang Bill Zhu, Tianqi Chen, Xinyan Velocity Yu, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-cancer-myth-evaluating-large-language/)
155. **[Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs](https://md.research.elamur.ai/free/en/papers/zhou-2026-flattery-motion-benchmarking-analyzing-sycophancy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenrui Zhou, Mohamed Hendy, Shu Yang, et al.*2026 · 6 citations*
156. **[Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs](https://md.research.elamur.ai/free/en/papers/siddique-2026-shifting-perspectives-steering-vectors-robust/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zara Siddique, Irtaza Khalid, Liam Turner, et al.*2026 · 6 citations*
157. **[Is Chain-of-Thought Really Not Explainability? Chain-of-Thought Can Be Faithful without Hint Verbalization](https://md.research.elamur.ai/free/en/papers/zaman-2026-is-chain-thought-really-not/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kerem Zaman, Shashank Srivastava*2026 · 5 citations*
158. **[Analysing Chain of Thought Dynamics: Active Guidance or Unfaithful Post-hoc Rationalisation?](https://md.research.elamur.ai/free/en/papers/lim-2025-analysing-chain-thought-dynamics-active/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao, et al.*2025 · 5 citations*
159. **[Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing](https://md.research.elamur.ai/free/en/papers/ulmer-2026-anthropomimetic-uncertainty-what-verbalized-uncertainty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dennis Ulmer, Alexandra Lorson, Ivan Titov, et al.*2026 · 4 citations*
160. **[Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken English](https://md.research.elamur.ai/free/en/papers/anderson-2025-model-misalignment-language-change-traces/) [Proceedings of the AAAI/ACM Conference on AI Ethics and Society](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-acm-conference-on-ai-ethics-and-society/)**Bryce Anderson, Riley Galpin, Tom S. Juzek*2025 · 4 citations*
161. [**What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT arXiv:2509.19284**Yunzhen Feng, Julia Kempe, Cheng Zhang, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-characterizes-effective-reasoning-revisiting-length/)
162. **[Confidence Should Be Calibrated More Than One Turn Deep](https://md.research.elamur.ai/free/en/papers/zhang-2026-confidence-should-be-calibrated-more/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaohan Zhang, Chengzhengxu Li, Xiaoming Liu, et al.*2026 · 3 citations*
163. **[Evaluating the Effect of Retrieval Augmentation on Social Biases](https://md.research.elamur.ai/free/en/papers/zhang-2026-evaluating-effect-retrieval-augmentation-social/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tianhui Zhang, Yi Zhou, Danushka Bollegala*2026 · 3 citations*
164. **[LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient](https://md.research.elamur.ai/free/en/papers/yuan-2026-llm-powered-benchmark-factory-reliable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiwen Yuan, Shaoxiong Feng, Yiwei Li, et al.*2026 · 3 citations*
165. **[Task Matters: Knowledge Requirements Shape LLM Responses to Context–Memory Conflict](https://md.research.elamur.ai/free/en/papers/sun-2026-task-matters-knowledge-requirements-shape/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiser Sun, Fan Bai, Mark Dredze*2026 · 3 citations*
166. **[Argument-Based Consistency in Toxicity Explanations of LLMs](https://md.research.elamur.ai/free/en/papers/mothilal-2026-argument-based-consistency-toxicity-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ramaravind Kommiya Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, et al.*2026 · 2 citations*
167. **[C2-Faith: Benchmarking LLM Judges for Causal and Coverage Faithfulness in Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/mittal-2026-c2-faith-benchmarking-llm-judges/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Avni Mittal, Rauno Arike*2026 · 2 citations*
168. **[Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-do-images-speak-louder-than/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chi Zhang, Wenxuan Ding, Jiale Liu, et al.*2026 · 2 citations*
169. **[Do LLMs Encode Functional Importance of Reasoning Tokens ?](https://md.research.elamur.ai/free/en/papers/singh-2026-do-llms-encode-functional-importance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Janvijay Singh, Dilek Hakkani-Tür*2026 · 2 citations*
170. **[From Belief Entrenchment to Robust Reasoning in LLM Agents](https://md.research.elamur.ai/free/en/papers/oh-2026-belief-entrenchment-robust-reasoning-llm/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jihwan Oh, Minchan Jeong, Jongwoo Ko, et al.*2026 · 2 citations*
171. **[From Fact to Judgment: Investigating the Impact of Task Framing on LLM Conviction in Dialogue Systems](https://md.research.elamur.ai/free/en/papers/rabbani-2026-fact-judgment-investigating-impact-task/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Parisa Rabbani, Nimet Beyza Bozdag, Dilek Hakkani-Tur*2026 · 2 citations*
172. **[Learning Multilingual Agentic Policy to Control Sycophancy](https://md.research.elamur.ai/free/en/papers/ranaldi-2026-learning-multilingual-agentic-policy-control/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Leonardo Ranaldi, Giulia Pucci*2026 · 2 citations*
173. **[LLM Reasoning as Trajectories: Step-Specific Representation Geometry and Correctness Signals](https://md.research.elamur.ai/free/en/papers/sun-2026-llm-reasoning-as-trajectories-step/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lihao Sun, Hang Dong, Bo Qiao, et al.*2026 · 2 citations*
174. **[Persona Jailbreaking in Large Language Models](https://md.research.elamur.ai/free/en/papers/sandhan-2026-persona-jailbreaking-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jivnesh Sandhan, Fei Cheng, Tushar Sandhan, et al.*2026 · 2 citations*
175. **[Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation](https://md.research.elamur.ai/free/en/papers/shen-2026-preconditioned-test-time-adaptation-out/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanwen Shen, Ting Ying, Jiajie Lu, et al.*2026 · 2 citations*
176. **[Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?](https://md.research.elamur.ai/free/en/papers/molfetta-2026-sycophants-courtroom-are-llms-fragile/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.*2026 · 2 citations*
177. **[A Comprehensive Evaluation of Chain-of-Thought Faithfulness in Persian Classification Tasks](https://md.research.elamur.ai/free/en/papers/yazdani-2026-comprehensive-evaluation-chain-thought-faithfulness/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Shakib Yazdani, Cristina España-Bonet, Eleftherios Avramidis, et al.*2026 · 1 citation*
178. **[Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors](https://md.research.elamur.ai/free/en/papers/yin-2026-compiling-activation-steering-into-weights/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Yin, Tianxu Han, Naen Xu, et al.*2026 · 1 citation*
179. **[Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors](https://md.research.elamur.ai/free/en/papers/zhao-2026-evaluating-robustness-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raoyuan Zhao, Yihong Liu, Lena Altinger, et al.*2026 · 1 citation*
180. **[Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation](https://md.research.elamur.ai/free/en/papers/wang-2026-exploring-graph-learning-tasks-pure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxiang Wang, Xinnan Dai, Wenqi Fan, et al.*2026 · 1 citation*
181. **[From “Thinking” to “Justifying”: Aligning High-Stakes Explainability with Professional Communication Standards](https://md.research.elamur.ai/free/en/papers/qian-2026-thinking-justifying-aligning-high-stakes/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chen Qian, Yimeng Wang, Yu Chen, et al.*2026 · 1 citation*
182. **[Meeseeks: A Feedback-Driven, Iterative Self-Correction Benchmark evaluating LLMs' Instruction Following Capability](https://md.research.elamur.ai/free/en/papers/wang-2026-meeseeks-feedback-driven-iterative-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Wang, Yunke Zhao, Peng Ding, et al.*2026 · 1 citation*
183. **[PARASITE: Conditional System Prompt Poisoning to Hijack LLMs](https://md.research.elamur.ai/free/en/papers/pham-2026-parasite-conditional-system-prompt-poisoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Viet Pham, Thai Le*2026 · 1 citation*
184. [**Position: Correct Answer, Wrong Mechanism — When AI Scientists Defend General Claims Their Own Data Contradicts arXiv:2606.23175**Steven Young Eulig*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/eulig-2026-position-correct-answer-wrong/)
185. [**PseudoBench: Measuring How Agentic Auto-Research Fuels Pseudoscience arXiv:2606.18060**Xinyang Liao, Lingyu Li, Huacan Liu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/liao-2026-pseudobench-measuring-agentic-auto/)
186. **[Purdah and Patriarchy: Evaluating and Mitigating South Asian Biases in Open-Ended Multilingual LLM Generations](https://md.research.elamur.ai/free/en/papers/rinki-2026-purdah-patriarchy-evaluating-mitigating-south/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Mamnuya Rinki, Chahat Raj, Anjishnu Mukherjee, et al.*2026 · 1 citation*
187. **[Reasoning Fails Where Step Flow Breaks](https://md.research.elamur.ai/free/en/papers/xu-2026-reasoning-fails-where-step-flow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Xu, Yulan Pan, Xiaosong Yuan, et al.*2026 · 1 citation*
188. **[Revealing Procedural Reasoning Structures in Chain-of-Thought Training via Span-Level Gradient Organization](https://md.research.elamur.ai/free/en/papers/liu-2026-revealing-procedural-reasoning-structures-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jia Liu, Jiaxin Luo, Weiwen Xu, et al.*2026 · 1 citation*
189. **[Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs](https://md.research.elamur.ai/free/en/papers/maraia-2026-sounding-vs-being-expert-disentangling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gabriele Maraia, Fabio Massimo Zanzotto, Leonardo Ranaldi*2026 · 1 citation*
190. **[SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/lv-2026-spd-faith-bench-diagnosing-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weijiang Lv, Yaoxuan Feng, Xiaobo Xia, et al.*2026 · 1 citation*
191. **[SycoBench-600: Measuring Sycophancy and Correction Selectivity in LLM Assistants](https://md.research.elamur.ai/free/en/papers/sinha-2026-sycobench-600-measuring-sycophancy-correction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Debu Sinha*2026 · 1 citation*
192. **[The Pluralistic Moral Gap: Understanding Moral Judgment and Value Differences between Humans and Large Language Models](https://md.research.elamur.ai/free/en/papers/russo-2026-pluralistic-moral-gap-understanding-moral/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Giuseppe Russo, Debora Nozza, Paul Röttger, et al.*2026 · 1 citation*
193. **[The Thin Line Between Comprehension and Persuasion in LLMs](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrian de Wynter, Tangming Yuan*2026 · 1 citation*
194. **[Training Language Models to Use Prolog as a Tool](https://md.research.elamur.ai/free/en/papers/mellgren-2026-training-language-models-use-prolog/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Niklas Mellgren, Peter Schneider-Kamp, Lukas Galke Poech*2026 · 1 citation*
195. **[Trajectory Signatures of Deception in Large Language Models](https://md.research.elamur.ai/free/en/papers/mothukuri-2026-trajectory-signatures-deception-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Viraaji Mothukuri, Reza M. Parizi*2026 · 1 citation*
196. **[Understanding and Mitigating Political Stance Cross-topic Generalization in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-understanding-mitigating-political-stance-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiayi Zhang, Shu Yang, Junchao Wu, et al.*2026 · 1 citation*
197. [**TracrBench: Generating Interpretability Testbeds with Large Language Models arXiv:2409.13714**Hannes Thurnherr, Jérémy Scheurer*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/thurnherr-2024-tracrbench-generating-interpretability-testbeds/)
198. **[AgriChain: Visually-Grounded Expert-Verified Reasoning for Interpretable Agricultural Vision–Language Models](https://md.research.elamur.ai/free/en/papers/mahmood-2026-agrichain-visually-grounded-expert-verified/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hazza Mahmood, Yongqiang Yu, Rao Anwer*2026*
199. **[At Your Own PACE: A Causal Framework for Evaluating EQ in LLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-your-own-pace-causal-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lei Lyu, Shengling Wang, Ke Chao, et al.*2026*
200. **[Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs](https://md.research.elamur.ai/free/en/papers/williams-2026-beyond-marginal-distributions-framework-evaluate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tristan Williams, Franziska Weeber, Sebastian Padó, et al.*2026*

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