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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

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  1. The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive ConversationarXiv:2312.09085Rongwu Xu, Brian S. Lin, Shujian Yang, et al.2023 · 56 citations
  2. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
  3. Tokenization counts: the impact of tokenization on arithmetic in frontier LLMsarXiv:2402.14903Aaditya K. Singh, DJ Strouse2024 · 55 citations
  4. In-context Learning with Retrieved Demonstrations for Language Models: A SurveyarXiv:2401.11624Man Luo, Xin Xu, Yue Liu, et al.2024 · 54 citations
  5. Chain-of-Thought Reasoning In The Wild Is Not Always FaithfularXiv:2503.08679Ivan Arcuschin, Jett Janiak, Robert Krzyzanowski, et al.2025 · 52 citations
  6. Critique-out-Loud Reward ModelsarXiv:2408.11791Zachary Ankner, Mansheej Paul, Brandon Cui, et al.2024 · 52 citations
  7. Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
  8. Formal Mathematical Reasoning: A New Frontier in AIarXiv:2412.16075Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.2024 · 49 citations
  9. Thought Anchors: Which LLM Reasoning Steps Matter?arXiv:2506.19143Paul C. Bogdan, Uzay Macar, Neel Nanda, et al.2025 · 44 citations
  10. Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model CollaborationarXiv:2310.00280Qiushi Sun, Zhangyue Yin, Xiang Li, et al.2023 · 41 citations
  11. SALMON: Self-Alignment with Instructable Reward ModelsarXiv:2310.05910Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.2023 · 41 citations
  12. DeepRAG: Thinking to Retrieve Step by Step for Large Language ModelsarXiv:2502.01142Xinyan Guan, Jiali Zeng, Fandong Meng, et al.2025 · 40 citations
  13. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
  14. Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and ParaphrasingarXiv:2305.16635Jaehun Jung, Peter West, Liwei Jiang, et al.2023 · 36 citations
  15. Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning GaparXiv:2402.19450Saurabh Srivastava, Annarose M B, Anto P, et al.2024 · 35 citations
  16. Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge EvaluationarXiv:2306.05783Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.2023 · 34 citations
  17. SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model SafetyarXiv:2404.05399Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.2024 · 33 citations
  18. Interpretable Unified Language CheckingarXiv:2304.03728Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.2023 · 32 citations
  19. Language Models as Science TutorsarXiv:2402.11111Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.2024 · 30 citations
  20. Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language ModelsarXiv:2310.00836Man Luo, Shrinidhi Kumbhar, Ming shen, et al.2023 · 27 citations
  21. Feedback Loops With Language Models Drive In-Context Reward HackingarXiv:2402.06627Alexander Pan, Erik Jones, Meena Jagadeesan, et al.2024 · 26 citations
  22. AI Sandbagging: Language Models can Strategically Underperform on EvaluationsarXiv:2406.07358Teun van der Weij, Felix Hofstatter, Ollie Jaffe, et al.2024 · 22 citations
  23. Quality-Diversity through AI FeedbackarXiv:2310.13032Herbie Bradley, Andrew Dai, Hannah Teufel, et al.2023 · 19 citations
  24. ChatGLM-RLHF: Practices of Aligning Large Language Models with Human FeedbackarXiv:2404.00934Zhenyu Hou, Yilin Niu, Zhengxiao Du, et al.2024 · 17 citations
  25. Aligning Large Language Models with Human Opinions through Persona Selection and Value — Belief — Norm ReasoningarXiv:2311.08385Do Xuan Long, Kenji Kawaguchi, Min-Yen Kan, et al.2023 · 12 citations
  26. Preventing Language Models From Hiding Their ReasoningarXiv:2310.18512Fabien Roger, Ryan Greenblatt2023 · 10 citations
  27. Cancer-Myth: Evaluating Large Language Models on Patient Questions with False PresuppositionsarXiv:2504.11373Wang Bill Zhu, Tianqi Chen, Xinyan Velocity Yu, et al.2025 · 7 citations
  28. What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoTarXiv:2509.19284Yunzhen Feng, Julia Kempe, Cheng Zhang, et al.2025 · 4 citations
  29. Argument-Based Consistency in Toxicity Explanations of LLMsFindings of the Association for Computational LinguisticsRamaravind Kommiya Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, et al.2026 · 2 citations
  30. Persona Jailbreaking in Large Language ModelsFindings of the Association for Computational LinguisticsJivnesh Sandhan, Fei Cheng, Tushar Sandhan, et al.2026 · 2 citations
  31. Position: Correct Answer, Wrong Mechanism — When AI Scientists Defend General Claims Their Own Data ContradictsarXiv:2606.23175Steven Young Eulig2026 · 1 citation
  32. PseudoBench: Measuring How Agentic Auto-Research Fuels PseudosciencearXiv:2606.18060Xinyang Liao, Lingyu Li, Huacan Liu, et al.2026 · 1 citation
  33. Training Language Models to Use Prolog as a ToolFindings of the Association for Computational LinguisticsNiklas Mellgren, Peter Schneider-Kamp, Lukas Galke Poech2026 · 1 citation
  34. TracrBench: Generating Interpretability Testbeds with Large Language ModelsarXiv:2409.13714Hannes Thurnherr, Jérémy Scheurer2024 · 1 citation

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