🧑‍🔬 Who cites Rachit Bansal

123 citations of their works from 122 papers of our library (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · ← Rachit Bansal

1. Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model SizesFindings of the Association for Computational LinguisticsCheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.2023 · 690 citations
2. Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 575 citations
3. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
4. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
5. Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and EvaluationFindings of the Association for Computational LinguisticsMarius Mosbach, Tiago Pimentel, Shauli Ravfogel, et al.2023 · 148 citations
6. Arcee's MergeKit: A Toolkit for Merging Large Language ModelsarXiv:2403.13257Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, et al.2024 · 105 citations
7. REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage NormalizationarXiv:2501.03262Jian Hu, Jason Klein Liu, Haotian Xu, et al.2025 · 104 citations
8. Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtConference on Empirical Methods in Natural Language Processing (EMNLP)Ori Yoran, Tomer Wolfson, Ben Bogin, et al.2023 · 99 citations
9. Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewardsConference on Neural Information Processing Systems (NeurIPS)Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.2023 · 90 citations
10. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
11. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
12. Deep Model Fusion: A SurveyIEEE Transactions on Neural Networks and Learning SystemsWeishi Li, Yong Peng, Miao Zhang, et al.2023 · 49 citations
13. LangBridge: Multilingual Reasoning Without Multilingual SupervisionAnnual Meeting of the Association for Computational Linguistics (ACL)Dongkeun Yoon, Joel Jang, Sungdong Kim, et al.2024 · 29 citations
14. Soft Merging of Experts with Adaptive RoutingarXiv:2306.03745Mohammed Muqeeth, Haokun Liu, Colin Raffel2023 · 24 citations
15. Can Authorship Representation Learning Capture Stylistic Features?Transactions of the Association for Computational Linguistics (TACL)Andrew Wang, Cristina Aggazzotti, Rebecca Kotula, et al.2023 · 21 citations
16. When One LLM Drools, Multi-LLM Collaboration RulesAnnual Meeting of the Association for Computational Linguistics (ACL)Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.2026 · 14 citations
17. Tailoring Self-Rationalizers with Multi-Reward DistillationInternational Conference on Learning Representations (ICLR)Sahana Ramnath, Brihi Joshi, Skyler Hallinan, et al.2023 · 14 citations
18. Multiple LLM Agents Debate for Equitable Cultural AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Dayeon Ki, Rachel Rudinger, Tianyi Zhou, et al.2025 · 10 citations
19. KL for a KL: On-Policy Distillation with Control Variate BaselinearXiv:2605.07865Minjae Oh, Sangjun Song, Gyubin Choi, et al.2026 · 8 citations
20. Cool-Fusion: Fuse Large Language Models without TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Cong Liu, Xiaojun Quan, Yan Pan, et al.2025 · 8 citations
21. Confidence Leaps in LLM Reasoning: Early Stopping and Cross-Model TransferConference of the European Chapter of the Association for Computational Linguistics (EACL)Pavel Tikhonov, Ivan Oseledets, Elena Tutubalina2026
22. One Pair Suffices: Unlocking Universal Zero-Shot Translation via Cross-Architecture AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Zong, Cong Hu Yuan, Chao Bei, et al.2026
23. The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAGAnnual Meeting of the Association for Computational Linguistics (ACL)Shu Zhou, Jinman Leng, Yufei Song, et al.2026

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