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Who cites Vikas Raunak

1,776 citations of their works from 1,699 papers of our library (of the 141,840 whose bibliographies we read) · 244 with a page here, the most cited first · page 2 of 3 · 101–200 · ← Vikas Raunak

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  1. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 207 citations
    Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Oded Ovadia, Menachem Brief, Moshik Mishaeli, et al.2024 · 206 citations
    On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Nouha Dziri, Sivan Milton, Mo Yu, et al.2022 · 205 citations
    Aya Dataset: An Open-Access Collection for Multilingual Instruction TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.2024 · 203 citations
  2. TinyStories: How Small Can Language Models Be and Still Speak Coherent English?Ronen Eldan, Yuanzhi Li2023 · 202 citations
    A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsFindings of the Association for Computational LinguisticsMd Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.2023 · 200 citations
  3. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 199 citations
  4. From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder PipelinearXiv:2406.11939Tianle Li, Wei-Lin Chiang, Evan Frick, et al.2024 · 191 citations
    Towards Making the Most of ChatGPT for Machine TranslationFindings of the Association for Computational LinguisticsKeqin Peng, Liang Ding, Qihuang Zhong, et al.2023 · 190 citations
  5. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 187 citations
  6. LawBench: Benchmarking Legal Knowledge of Large Language ModelsarXiv:2309.16289Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, et al.2023 · 186 citations
    On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Omar Shaikh, Hongxin Zhang, William Held, et al.2023 · 180 citations
  7. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 178 citations
    LILA: A Unified Benchmark for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.2022 · 177 citations
    LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic ProversConference on Empirical Methods in Natural Language Processing (EMNLP)Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.2023 · 171 citations
  8. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 170 citations
    The Troubling Emergence of Hallucination in Large Language Models - An Extensive Definition, Quantification, and Prescriptive RemediationsConference on Empirical Methods in Natural Language Processing (EMNLP)Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, et al.2023 · 170 citations
  9. Low-Resource Languages Jailbreak GPT-4arXiv:2310.02446Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach2023 · 168 citations
  10. Generative Representational Instruction TuningarXiv:2402.09906Niklas Muennighoff, Hongjin Su, Liang Wang, et al.2024 · 165 citations
  11. BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex InstructionsarXiv:2406.15877Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.2024 · 163 citations
  12. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  13. Orca 2: Teaching Small Language Models How to ReasonarXiv:2311.11045Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.2023 · 160 citations
    LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt CompressionFindings of the Association for Computational LinguisticsZhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.2024 · 159 citations
    When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 159 citations
    DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 156 citations
    Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors PersistConference on Machine Translation (WMT)Marzena Karpinska, Mohit Iyyer2023 · 156 citations
    ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Justin Chen, Swarnadeep Saha, Mohit Bansal2024 · 154 citations
    ChatGPT MT: Competitive for High- (but Not Low-) Resource LanguagesConference on Machine Translation (WMT)Nathaniel Robinson, Perez Ogayo, David R. Mortensen, et al.2023 · 151 citations
    Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
    Measure and Improve Robustness in NLP Models: A SurveyConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xuezhi Wang, Haohan Wang, Diyi Yang2022 · 148 citations
    Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine TranslationConference of the European Chapter of the Association for Computational Linguistics (EACL)Nuno M. Guerreiro, Elena Voita, André Martins2023 · 147 citations
  14. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 145 citations
    Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 145 citations
    Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
  15. Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-CollaborationarXiv:2307.05300Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.2023 · 139 citations
    FaithDial: A Faithful Benchmark for Information-Seeking DialogueTransactions of the Association for Computational Linguistics (TACL)Nouha Dziri, Ehsan Kamalloo, Sivan Milton, et al.2022 · 138 citations
  16. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 135 citations
    Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language ModelsFindings of the Association for Computational LinguisticsQingyu Lu, Baopu Qiu, Liang Ding, et al.2024 · 135 citations
    Self-Knowledge Guided Retrieval Augmentation for Large Language ModelsFindings of the Association for Computational LinguisticsYile Wang, Peng Li, Maosong Sun, et al.2023 · 135 citations
    InFoBench: Evaluating Instruction Following Ability in Large Language ModelsFindings of the Association for Computational LinguisticsYiwei Qin, Kaiqiang Song, Yebowen Hu, et al.2024 · 133 citations
  17. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 133 citations
    FLUTE: Figurative Language Understanding through Textual ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.2022 · 132 citations
    Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology ViewAnnual Meeting of the Association for Computational Linguistics (ACL)Jintian Zhang, Xin Xu, Ningyu Zhang, et al.2024 · 131 citations
    Faithful Logical Reasoning via Symbolic Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Liangming Pan, et al.2024 · 129 citations
    Findings of the WMT 2023 Shared Task on Quality EstimationConference on Machine Translation (WMT)Frederic Blain, Chrysoula Zerva, Ricardo Rei, et al.2023 · 129 citations
    ZeroSCROLLS: A Zero-Shot Benchmark for Long Text UnderstandingFindings of the Association for Computational LinguisticsUri Shaham, Maor Ivgi, Avia Efrat, et al.2023 · 129 citations
    Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
    Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 128 citations
  18. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 128 citations
  19. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow InstructionsarXiv:2309.07875Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.2023 · 124 citations
  20. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 123 citations
    Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across LanguagesConference on Empirical Methods in Natural Language Processing (EMNLP)Libo Qin, Qiguang Chen, Fuxuan Wei, et al.2023 · 122 citations
  21. Large Language Models Understand and Can be Enhanced by Emotional StimuliarXiv:2307.11760Cheng Li, Jindong Wang, Yixuan Zhang, et al.2023 · 114 citations
    Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 113 citations
    LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 110 citations
    GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, et al.2023 · 110 citations
  22. Benchmarking Machine Translation with Cultural AwarenessarXiv:2305.14328Binwei Yao, Ming Jiang, Tara Bobinac, et al.2023 · 109 citations
  23. Evaluating the Performance of Large Language Models on GAOKAO BenchmarkarXiv:2305.12474Xiaotian Zhang, Chunyang Li, Yi Zong, et al.2023 · 109 citations
    Leveraging GPT-4 for Automatic Translation Post-EditingFindings of the Association for Computational LinguisticsVikas Raunak, Amr Sharaf, Yiren Wang, et al.2023 · 107 citations
  24. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 101 citations
    Eliciting the Translation Ability of Large Language Models via Multilingual Finetuning with Translation InstructionsTransactions of the Association for Computational Linguistics (TACL)Jiahuan Li, Hao Zhou, Shujian Huang, et al.2024 · 99 citations
  25. Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 99 citations
    Do Multilingual Language Models Think Better in English?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Julen Etxaniz, Gorka Azkune, Aitor Soroa, et al.2024 · 98 citations
  26. WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the WildarXiv:2406.04770Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.2024 · 95 citations
    Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
    MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 94 citations
  27. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 94 citations
    LLMs Are Few-Shot In-Context Low-Resource Language LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Samuel Cahyawijaya, Holy Lovenia, Pascale Fung2024 · 92 citations
  28. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 92 citations
    PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM InferenceFindings of the Association for Computational LinguisticsDongjie Yang, Xiaodong Han, Yan Gao, et al.2024 · 91 citations
    WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 89 citations
    “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language ModelsFindings of the Association for Computational LinguisticsXinpeng Wang, Bolei Ma, Chengzhi Hu, et al.2024 · 89 citations
  29. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 88 citations
    NLPositionality: Characterizing Design Biases of Datasets and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.2023 · 88 citations
  30. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 85 citations
    LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations
    SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Zhengyuan Liu, Xin Huang, et al.2024 · 85 citations
  31. Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOMarXiv:2303.01911Rachel Bawden, François Yvon2023 · 85 citations
    NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationNorthern European Journal of Language TechnologyKaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.2023 · 85 citations
    ORCA: A Challenging Benchmark for Arabic Language UnderstandingFindings of the Association for Computational LinguisticsAbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed2023 · 83 citations
    Style Over Substance: Evaluation Biases for Large Language ModelsInternational Conference on Computational Linguistics (COLING)Minghao Wu, Alham Fikri Aji2025 · 77 citations
    KoBBQ: Korean Bias Benchmark for Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Jiho Jin, Jiseon Kim, Nayeon Lee, et al.2024 · 77 citations
  32. PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics CapabilitiesSettaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.2024 · 75 citations
    MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and TasksConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.2024 · 74 citations
    AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.2024 · 73 citations
  33. INCLUDE: Evaluating Multilingual Language Understanding with Regional KnowledgearXiv:2411.19799Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.2024 · 73 citations
    Iterative Translation Refinement with Large Language ModelsAnnual Conference of the European Association for Machine Translation (EAMT)Pinzhen Chen, Zhicheng Guo, Barry Haddow, et al.2024 · 73 citations
  34. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsarXiv:2311.18743Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.2023 · 73 citations
    KMMLU: Measuring Massive Multitask Language Understanding in KoreanConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guijin Son, Hanwool Lee, Sungdong Kim, et al.2025 · 72 citations
    MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical ReasoningConference on Neural Information Processing Systems (NeurIPS)Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.2024 · 70 citations
    IrokoBench: A New Benchmark for African Languages in the Age of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, et al.2025 · 69 citations
  35. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 69 citations
    Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsFindings of the Association for Computational LinguisticsAlfonso Amayuelas, Kyle Wong, Liangming Pan, et al.2024 · 66 citations
  36. CValues: Measuring the Values of Chinese Large Language Models from Safety to ResponsibilityarXiv:2307.09705Guohai Xu, Jiayi Liu, Ming Yan, et al.2023 · 63 citations
  37. Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use CasesarXiv:2303.14742Yunjie Ji, Yong Deng, Yan Gong, et al.2023 · 62 citations
    Understanding Transformer Memorization Recall Through IdiomsConference of the European Chapter of the Association for Computational Linguistics (EACL)Adi Haviv, Ido Cohen, Jacob Gidron, et al.2023 · 62 citations
  38. Large Language Model Routing with Benchmark DatasetsarXiv:2309.15789Tal Shnitzer, Anthony Ou, Mirian Silva, et al.2023 · 61 citations
    TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic VarietiesArabic Natural Language Processing Conference (ArabicNLP)Karima Kadaoui, Samar M. Magdy, Abdul Waheed, et al.2023 · 60 citations
  39. CMB: A Comprehensive Medical Benchmark in ChinesearXiv:2308.08833Xidong Wang, Guiming Hardy Chen, Dingjie Song, et al.2023 · 54 citations
  40. Language acquisition: do children and language models follow similar learning stages?arXiv:2306.03586Linnea Evanson, Yair Lakretz, Jean-Rémi King2023 · 53 citations

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