---
title: "Who cites Eric Zelikman — page 2 — 1,551 papers of our library"
description: "1,551 papers of the Elamur Research library cite the works of Eric Zelikman, found in their bibliographies · page 2 of 5 · 101–200; the most…"
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---
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# Who cites Eric Zelikman

1,597 citations of their works from 1,551 papers of our library (of the 149,439 whose bibliographies we read) · 458 with a page here, the most cited first · page 2 of 5 · 101–200 · [← Eric Zelikman](https://md.research.elamur.ai/free/en/authors/eric-zelikman/)

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101. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 191 citations*
102. [**LawBench: Benchmarking Legal Knowledge of Large Language Models arXiv:2309.16289**Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.*2023 · 186 citations*](https://md.research.elamur.ai/free/en/papers/fei-2023-lawbench-benchmarking-legal-knowledge-large/)
103. **[Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time](https://md.research.elamur.ai/free/en/papers/liu-2023-deja-vu-contextual-sparsity-efficient/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Zichang Liu, Jue Wang, Tri Dao, et al.*2023 · 185 citations*
104. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
105. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
106. [**Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution arXiv:2309.16797**Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.*2023 · 174 citations*](https://md.research.elamur.ai/free/en/papers/fernando-2023-promptbreeder-self-referential-self-improvement/)
107. **[LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 172 citations*
108. **[FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts](https://md.research.elamur.ai/free/en/papers/gong-2023-figstep-jailbreaking-large-vision-language/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yichen Gong, Delong Ran, Jinyuan Liu, et al.*2023 · 163 citations*
109. [**Language models show human-like content effects on reasoning tasks arXiv:2207.07051**Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, et al.*2022 · 162 citations*](https://md.research.elamur.ai/free/en/papers/dasgupta-2022-language-models-show-human-like/)
110. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 161 citations*
111. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
112. [**SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training arXiv:2501.17161**Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.*2025 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chu-2025-sft-memorizes-rl-generalizes-comparative/)
113. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
114. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/)
115. **[Large Language Models with Controllable Working Memory](https://md.research.elamur.ai/free/en/papers/li-2023-large-language-models-controllable-working/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.*2023 · 158 citations*
116. **[Are aligned neural networks adversarially aligned?](https://md.research.elamur.ai/free/en/papers/carlini-2023-aligned-neural-networks-adversarially-aligned/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.*2023 · 157 citations*
117. **[ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs](https://md.research.elamur.ai/free/en/papers/chen-2024-reconcile-round-table-conference-improves/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Justin Chen, Swarnadeep Saha, Mohit Bansal*2024 · 156 citations*
118. [**REFINER: Reasoning Feedback on Intermediate Representations arXiv:2304.01904**Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/paul-2023-refiner-reasoning-feedback-intermediate-representations/)
119. [**ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning arXiv:2212.07919**Olga Golovneva, Moya Chen, Spencer Poff, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/golovneva-2022-roscoe-suite-metrics-scoring-step/)
120. [**Can GPT-3 Perform Statutory Reasoning? arXiv:2302.06100**Andrew Blair-Stanek, Nils Holzenberger, Benjamin Van Durme*2023 · 154 citations*](https://md.research.elamur.ai/free/en/papers/blair-stanek-2023-gpt-3-perform-statutory-reasoning/)
121. **[Iterative Reasoning Preference Optimization](https://md.research.elamur.ai/free/en/papers/pang-2024-iterative-reasoning-preference-optimization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.*2024 · 153 citations*
122. [**Generative Verifiers: Reward Modeling as Next-Token Prediction arXiv:2408.15240**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 152 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
123. [**Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation arXiv:2305.15852**Niels Mundler, Jingxuan He, Slobodan Jenko, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/mundler-2023-self-contradictory-hallucinations-large-language/)
124. **[Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2024-draft-verify-lossless-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jun Zhang, Jue Wang, Huan Li, et al.*2024 · 148 citations*
125. **[Instruction Induction: From Few Examples to Natural Language Task Descriptions](https://md.research.elamur.ai/free/en/papers/honovich-2022-instruction-induction-few-examples-natural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or Honovich, Uri Shaham, Samuel R. Bowman, et al.*2022 · 148 citations*
126. [**Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models arXiv:2312.06585**Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/singh-2023-human-data-scaling-self-training/)
127. [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges arXiv:2310.17631**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/)
128. [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
129. [**Rethinking with Retrieval: Faithful Large Language Model Inference arXiv:2301.00303**Hangfeng He, Hongming Zhang, Dan Roth*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-rethinking-retrieval-faithful-large-language/)
130. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention arXiv:2502.11089**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 142 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)
131. [**SLiC-HF: Sequence Likelihood Calibration with Human Feedback arXiv:2305.10425**Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-slic-hf-sequence-likelihood-calibration/)
132. **[Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies](https://md.research.elamur.ai/free/en/papers/pan-2024-automatically-correcting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Liangming Pan, Michael Saxon, Wenda Xu, et al.*2024 · 140 citations*
133. **[Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step](https://md.research.elamur.ai/free/en/papers/li-2023-symbolic-chain-thought-distillation-small/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.*2023 · 140 citations*
134. [**SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents arXiv:2310.11667**Xuhui Zhou, Hao Zhu, Leena Mathur, et al.*2023 · 138 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-sotopia-interactive-evaluation-social-intelligence/)
135. **[InFoBench: Evaluating Instruction Following Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/qin-2024-infobench-evaluating-instruction-following-ability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiwei Qin, Kaiqiang Song, Yebowen Hu, et al.*2024 · 136 citations*
136. **[The Impact of Positional Encoding on Length Generalization in Transformers](https://md.research.elamur.ai/free/en/papers/kazemnejad-2023-impact-positional-encoding-length-generalization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, et al.*2023 · 134 citations*
137. **[Few-Shot Self-Rationalization with Natural Language Prompts](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ana Marasovic, Iz Beltagy, Doug Downey, et al.*2022 · 134 citations*
138. [**Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback arXiv:2305.10142**Yao Fu, Hao Peng, Tushar Khot, et al.*2023 · 132 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/)
139. **[ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding](https://md.research.elamur.ai/free/en/papers/shaham-2023-zeroscrolls-zero-shot-benchmark-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Uri Shaham, Maor Ivgi, Avia Efrat, et al.*2023 · 132 citations*
140. **[Natural Language Reasoning, A Survey](https://md.research.elamur.ai/free/en/papers/yu-2023-natural-language-reasoning-survey/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Fei Yu, Hongbo Zhang, Prayag Tiwari, et al.*2023 · 130 citations*
141. [**Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning arXiv:2303.15647**Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-scaling-down-scale-up-guide/)
142. **[Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data](https://md.research.elamur.ai/free/en/papers/shum-2023-automatic-prompt-augmentation-selection-chain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kashun Shum, Shizhe Diao, Tong Zhang*2023 · 128 citations*
143. [**Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future arXiv:2309.15402**Zheng Chu, Jingchang Chen, Qianglong Chen, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-navigate-through-enigmatic-labyrinth-survey/)
144. **[Can Language Models Solve Graph Problems in Natural Language?](https://md.research.elamur.ai/free/en/papers/wang-2023-language-models-solve-graph-problems/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heng Wang, Shangbin Feng, Tianxing He, et al.*2023 · 124 citations*
145. [**H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models arXiv:2306.14048**Zhenyu Zhang, Ying Sheng, Tianyi Zhou, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-h-2-o-heavy-hitter/)
146. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
147. **[Unlearn What You Want to Forget: Efficient Unlearning for LLMs](https://md.research.elamur.ai/free/en/papers/chen-2023-unlearn-what-you-want-forget/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaao Chen, Diyi Yang*2023 · 124 citations*
148. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
149. **[LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal Domain](https://md.research.elamur.ai/free/en/papers/niklaus-2023-lextreme-multi-lingual-multi-task/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joel Niklaus, Veton Matoshi, Pooja Rani, et al.*2023 · 123 citations*
150. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/)
151. **[Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages](https://md.research.elamur.ai/free/en/papers/qin-2023-cross-lingual-prompting-improving-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Libo Qin, Qiguang Chen, Fuxuan Wei, et al.*2023 · 122 citations*
152. [**Faithful Reasoning Using Large Language Models arXiv:2208.14271**Antonia Creswell, Murray Shanahan*2022 · 122 citations*](https://md.research.elamur.ai/free/en/papers/creswell-2022-faithful-reasoning-using-large-language/)
153. [**Explanations from Large Language Models Make Small Reasoners Better arXiv:2210.06726**Shiyang Li, Jianshu Chen, Yelong Shen, et al.*2022 · 120 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-explanations-large-language-models-make/)
154. [**Demystifying Long Chain-of-Thought Reasoning in LLMs arXiv:2502.03373**Edward Yeo, Yuxuan Tong, Morry Niu, et al.*2025 · 119 citations*](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/)
155. [**Llumnix: Dynamic Scheduling for Large Language Model Serving OSDI 2024**Biao Sun, Ziming Huang, Hanyu Zhao, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-llumnix-dynamic-scheduling-large-language/)
156. **[Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors](https://md.research.elamur.ai/free/en/papers/zhang-2023-aligning-instruction-tasks-unlocks-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Zhang, Bernal Jimenez Gutierrez, Yu Su*2023 · 118 citations*
157. **[The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning](https://md.research.elamur.ai/free/en/papers/kim-2023-cot-collection-improving-zero-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Seungone Kim, Se Joo, Doyoung Kim, et al.*2023 · 118 citations*
158. [**Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation arXiv:2212.07981**Yixin Liu, Alexander R. Fabbri, Pengfei Liu, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-revisiting-gold-standard-grounding-summarization/)
159. [**Med-Flamingo: a Multimodal Medical Few-shot Learner arXiv:2307.15189**Michael Moor, Qian Huang, Shirley Wu, et al.*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/moor-2023-med-flamingo-multimodal-medical-few/)
160. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
161. [**V-STaR: Training Verifiers for Self-Taught Reasoners arXiv:2402.06457**Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2024-v-star-training-verifiers-self/)
162. **[RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors](https://md.research.elamur.ai/free/en/papers/dugan-2024-raid-shared-benchmark-robust-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liam Dugan, Alyssa Hwang, Filip Trhlík, et al.*2024 · 110 citations*
163. [**INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection arXiv:2402.03744**Chao Chen, Kai Liu, Ze Chen, et al.*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-inside-llms-internal-states-retain/)
164. **[Leveraging GPT-4 for Automatic Translation Post-Editing](https://md.research.elamur.ai/free/en/papers/raunak-2023-leveraging-gpt-4-automatic-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Vikas Raunak, Amr Sharaf, Yiren Wang, et al.*2023 · 108 citations*
165. **[Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?](https://md.research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qineng Wang, Zihao Wang, Ying Su, et al.*2024 · 107 citations*
166. **[Benchmarking Foundation Models with Language-Model-as-an-Examiner](https://md.research.elamur.ai/free/en/papers/bai-2023-benchmarking-foundation-models-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yushi Bai, Jiahao Ying, Yixin Cao, et al.*2023 · 106 citations*
167. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
168. **[Disentangling Length from Quality in Direct Preference Optimization](https://md.research.elamur.ai/free/en/papers/park-2024-disentangling-length-quality-direct-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ryan Park, Rafael Rafailov, Stefano Ermon, et al.*2024 · 105 citations*
169. [**Inverse Scaling: When Bigger Isn't Better arXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQF**Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.*2023 · 105 citations*](https://md.research.elamur.ai/free/en/papers/mckenzie-2023-inverse-scaling-bigger-isn-t/)
170. **[The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity](https://md.research.elamur.ai/free/en/papers/shojaee-2025-illusion-thinking-understanding-strengths-limitations/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.*2025 · 104 citations*
171. [**Model evaluation for extreme risks arXiv:2305.15324**Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/shevlane-2023-model-evaluation-extreme-risks/)
172. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
173. **[BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting](https://md.research.elamur.ai/free/en/papers/yong-2023-bloom-1-adding-language-support/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.*2023 · 102 citations*
174. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
175. [**Rationale-Augmented Ensembles in Language Models arXiv:2207.00747**Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.*2022 · 101 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-rationale-augmented-ensembles-language-models/)
176. [**Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security arXiv:2401.05459**Yuanchun Li, Hao Wen, Weijun Wang, et al.*2024 · 100 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-personal-llm-agents-insights-survey/)
177. [**FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets arXiv:2307.10928**Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.*2023 · 100 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-flask-fine-grained-language-model/)
178. **[ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/chen-2025-research-learning-reason-search-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mingyang Chen, Linzhuang Sun, Tianpeng Li, et al.*2025 · 99 citations*
179. **[Answering Questions by Meta-Reasoning over Multiple Chains of Thought](https://md.research.elamur.ai/free/en/papers/yoran-2023-answering-questions-meta-reasoning-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ori Yoran, Tomer Wolfson, Ben Bogin, et al.*2023 · 99 citations*
180. **[FELM: Benchmarking Factuality Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2023-felm-benchmarking-factuality-evaluation-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shiqi Chen, Yiran Zhao, Jinghan Zhang, et al.*2023 · 99 citations*
181. **[OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset](https://md.research.elamur.ai/free/en/papers/toshniwal-2024-openmathinstruct-1-1-8-million/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, et al.*2024 · 98 citations*
182. [**Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models arXiv:2601.18734**Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.*2026 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/)
183. [**A Survey of Confidence Estimation and Calibration in Large Language Models arXiv:2311.08298**Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.*2023 · 97 citations*](https://md.research.elamur.ai/free/en/papers/geng-2023-survey-confidence-estimation-calibration-large/)
184. [**TextGrad: Automatic "Differentiation" via Text arXiv:2406.07496**Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/yuksekgonul-2024-textgrad-automatic-differentiation-text/)
185. [**Teaching Algorithmic Reasoning via In-context Learning arXiv:2211.09066**Hattie Zhou, Azade Nova, Hugo Larochelle, et al.*2022 · 96 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-teaching-algorithmic-reasoning-context-learning/)
186. **[On Learning to Summarize with Large Language Models as References](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yixin Liu, Kejian Shi, Katherine He, et al.*2024 · 94 citations*
187. **[Do-Not-Answer: Evaluating Safeguards in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2024-do-not-answer-evaluating-safeguards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxia Wang, Haonan Li, Xudong Han, et al.*2024 · 93 citations*
188. **[LLMs Are Few-Shot In-Context Low-Resource Language Learners](https://md.research.elamur.ai/free/en/papers/cahyawijaya-2024-llms-are-few-shot-context/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Samuel Cahyawijaya, Holy Lovenia, Pascale Fung*2024 · 93 citations*
189. [**Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning arXiv:2410.08146**Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.*2024 · 93 citations*](https://md.research.elamur.ai/free/en/papers/setlur-2024-rewarding-progress-scaling-automated-process/)
190. [**On the Tool Manipulation Capability of Open-source Large Language Models arXiv:2305.16504**Qiantong Xu, Fenglu Hong, Bo Li, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-tool-manipulation-capability-open-source/)
191. **[“My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-my-answer-is-c-first/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinpeng Wang, Bolei Ma, Chengzhi Hu, et al.*2024 · 91 citations*
192. **[SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research](https://md.research.elamur.ai/free/en/papers/sun-2023-scieval-multi-level-large-language/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Liangtai Sun, Yang Han, Zihan Zhao, et al.*2023 · 91 citations*
193. [**InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning arXiv:2402.06332**Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.*2024 · 90 citations*](https://md.research.elamur.ai/free/en/papers/ying-2024-internlm-math-open-math-large/)
194. [**AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models arXiv:2310.15140**Sicheng Zhu, Ruiyi Zhang, Bang An, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-autodan-interpretable-gradient-based-adversarial/)
195. [**Automated Design of Agentic Systems arXiv:2408.08435**Shengran Hu, Cong Lu, Jeff Clune*2024 · 89 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-automated-design-agentic-systems/)
196. **[Evaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence Tasks](https://md.research.elamur.ai/free/en/papers/sottana-2023-evaluation-metrics-era-gpt-4/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andrea Sottana, Bin Liang, Kai Zou, et al.*2023 · 89 citations*
197. **[LAMBADA: Backward Chaining for Automated Reasoning in Natural Language](https://md.research.elamur.ai/free/en/papers/kazemi-2023-lambada-backward-chaining-automated-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mehran Kazemi, Najoung Kim, Deepti Bhatia, et al.*2023 · 89 citations*
198. [**Language Model Cascades arXiv:2207.10342**David Dohan, Winnie Xu, Aitor Lewkowycz, et al.*2022 · 89 citations*](https://md.research.elamur.ai/free/en/papers/dohan-2022-language-model-cascades/)
199. [**Large Language Models as General Pattern Machines arXiv:2307.04721**Suvir Mirchandani, Fei Xia, Pete Florence, et al.*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/mirchandani-2023-large-language-models-general-pattern/)
200. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)

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