🧑‍🔬 Who cites Ankit Singh Rawat

174 citations of their works from 174 papers of our library (of the 149,439 whose bibliographies we read) · 42 with a page here, the most cited first · ← Ankit Singh Rawat

1. A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
2. RoFormer: Enhanced Transformer with Rotary Position EmbeddingarXiv:2104.09864Jianlin Su, Yu Lu, Shengfeng Pan, et al.2021 · 3,028 citations
3. Big Bird: Transformers for Longer SequencesConference on Neural Information Processing Systems (NeurIPS)Manzil Zaheer, Guru Guruganesh, Avinava Dubey, et al.2020 · 1,023 citations
4. A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language ModelsACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li2024 · 1,010 citations
5. Benchmarking Large Language Models in Retrieval-Augmented GenerationProceedings of the AAAI Conference on Artificial IntelligenceJiawei Chen, Hongyu Lin, Xianpei Han, et al.2023 · 629 citations
6. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
7. Hallucination is Inevitable: An Innate Limitation of Large Language ModelsarXiv:2401.11817Ziwei Xu, Sanjay Jain, Mohan Kankanhalli2024 · 312 citations
8. What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 236 citations
9. What Can Transformers Learn In-Context? A Case Study of Simple Function ClassesConference on Neural Information Processing Systems (NeurIPS)Shivam Garg, Dimitris Tsipras, Percy Liang, et al.2022 · 209 citations
10. Making Retrieval-Augmented Language Models Robust to Irrelevant ContextarXiv:2310.01558Ori Yoran, Tomer Wolfson, Ori Ram, et al.2023 · 195 citations
11. RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language ModelsarXiv:2310.00746Zekun Moore Wang, Zhongyuan Peng, Haoran Que, et al.2023 · 187 citations
12. Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 182 citations
13. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
14. Context-faithful Prompting for Large Language ModelsFindings of the Association for Computational LinguisticsWenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.2023 · 148 citations
15. On the Ability and Limitations of Transformers to Recognize Formal LanguagesConference on Empirical Methods in Natural Language Processing (EMNLP)Satwik Bhattamishra, Kabir Ahuja, Navin Goyal2020 · 113 citations
16. R-Tuning: Instructing Large Language Models to Say ‘I Don't Know'Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hanning Zhang, Shizhe Diao, Yong Lin, et al.2024 · 99 citations
17. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
18. DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Ella Neeman, Roee Aharoni, Or Honovich, et al.2023 · 85 citations
19. HalluLens: LLM Hallucination BenchmarkAnnual Meeting of the Association for Computational Linguistics (ACL)Yejin Bang, Ziwei Ji, Alan Schelten, et al.2025 · 82 citations
20. Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Feiteng Fang, Yuelin Bai, Shiwen Ni, et al.2024 · 75 citations
21. Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit ComplexityTransactions of the Association for Computational Linguistics (TACL)Yiding Hao, Dana Angluin, Robert Frank2022 · 62 citations
22. Teaching Arithmetic to Small TransformersarXiv:2307.03381Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, et al.2023 · 57 citations
23. Resolving Knowledge Conflicts in Large Language ModelsarXiv:2310.00935Yike Wang, Shangbin Feng, Heng Wang, et al.2023 · 48 citations
24. Improving Retrieval Augmented Language Model with Self-ReasoningProceedings of the AAAI Conference on Artificial IntelligenceYuan Xia, Jingbo Zhou, Zhenhui Shi, et al.2024 · 32 citations
25. FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Qinggang Zhang, Zhishang Xiang, Yilin Xiao, et al.2025 · 27 citations
26. The Distracting Effect: Understanding Irrelevant Passages in RAGAnnual Meeting of the Association for Computational Linguistics (ACL)Chen Amiraz, Florin Cuconasu, Simone Filice, et al.2025 · 21 citations
27. Understanding the Dark Side of LLMs' Intrinsic Self-CorrectionAnnual Meeting of the Association for Computational Linguistics (ACL)Qingjie Zhang, Di Wang, Haoting Qian, et al.2025 · 21 citations
28. Source-Aware Training Enables Knowledge Attribution in Language ModelsarXiv:2404.01019Muhammad Khalifa, David Wadden, Emma Strubell, et al.2024 · 21 citations
29. Improving Multilingual Retrieval-Augmented Language Models through Dialectic Reasoning ArgumentationsConference on Empirical Methods in Natural Language Processing (EMNLP)Leonardo Ranaldi, Federico Ranaldi, Fabio Massimo Zanzotto, et al.2025 · 12 citations
30. Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Yongxin Xu, Ruizhe Zhang, Xinke Jiang, et al.2025 · 9 citations
31. PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question AnsweringWookje Han, Jinsol Park, Kyungjae Lee2023 · 4 citations
32. A Review of Incorporating Psychological Theories in LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zizhou Liu, Ziwei Gong, Lin Ai, et al.2026 · 1 citation
33. Knowing When Not to Answer: Lightweight KB-Aligned OOD Detection for Safe RAGAnnual Meeting of the Association for Computational Linguistics (ACL)Ilias Triantafyllopoulos, Renyi Qu, Salvatore Giorgi, et al.2026 · 1 citation
34. Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute ScalingFindings of the Association for Computational LinguisticsIvan Rodkin, Daniil Orel, Konstantin Smirnov, et al.2026
35. CoDA: Restoring Contextual Dominance via Copy-Encouraged Attention Intervention for Mitigating RAG HallucinationsFindings of the Association for Computational LinguisticsJinWei Shi, Qizhuo Xie, Qianzi Hou, et al.2026
36. DKME: Rethinking Coupled Knowledge Memory for Lifelong Model Editing of Large Language ModelsFindings of the Association for Computational LinguisticsGuanyu Zheng, Wang Zhenyu, He Tingting, et al.2026
37. Do Transformers Grok Succinct Algorithms? Mechanistic Evidence for Counting CircuitsFindings of the Association for Computational LinguisticsYizheng Zhao2026
38. GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy InputsFindings of the Association for Computational LinguisticsZhengxin Zhang, Chengyu Huang, Xufu Liu, et al.2026
39. Language Acquisition Device in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Masato Mita, Taiga Someya, Ryo Yoshida, et al.2026
40. LOKA: Conflict-Aware LLM Knowledge Update with Adaptive Knowledge MemoryAnnual Meeting of the Association for Computational Linguistics (ACL)Binchi Zhang, Zhengzhang Chen, Zaiyi Zheng, et al.2026
41. SCOPE: Boosting LLM Efficiency with Scoped Position EncodingAnnual Meeting of the Association for Computational Linguistics (ACL)Qingguo Qi, Hongyang Chen, Zhao Li2026
42. Understanding the Prompt SensitivityAnnual Meeting of the Association for Computational Linguistics (ACL)Yang Liu, Chenhui Chu2026

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