Who cites Melanie Subbiah
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- Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionarXiv:2302.12173Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, et al.2023 · 239 citations
- LexGLUE: A Benchmark Dataset for Legal Language Understanding in EnglishAnnual Meeting of the Association for Computational Linguistics (ACL)Ilias Chalkidis, Abhik Jana, Dirk Hartung, et al.2022 · 239 citations
- FUDGE: Controlled Text Generation With Future DiscriminatorsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kevin Yang, Dan Klein2021 · 239 citations
- COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge GraphsJena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, et al.2020 · 239 citations
- Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic TriggerAnnual Meeting of the Association for Computational Linguistics (ACL)Fanchao Qi, Mukai Li, Yangyi Chen, et al.2021 · 238 citations
- TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
- Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human SupervisionConference on Neural Information Processing Systems (NeurIPS)Zhiqing Sun, Yikang Shen, Qinhong Zhou, et al.2023 · 236 citations
- What learning algorithm is in-context learning? Investigations with linear modelsarXiv:2211.15661Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.2022 · 236 citations
- Detecting and Preventing Hallucinations in Large Vision Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceAnisha Gunjal, Jihan Yin, Erhan Bas2023 · 235 citations
- Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical StudyACM International Conference on Web Search and Data Mining (WSDM)Yuan Sui, Mengyu Zhou, Mingjie Zhou, et al.2023 · 235 citations
- Automatically Identifying Words That Can Serve as Labels for Few-Shot Text ClassificationInternational Conference on Computational Linguistics (COLING)Timo Schick, Helmut Schmid, Hinrich Schütze2020 · 234 citations
- Evaluating Open-Domain Question Answering in the Era of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ehsan Kamalloo, Nouha Dziri, Charles Clarke, et al.2023 · 233 citations
- Steering Language Models With Activation EngineeringarXiv:2308.10248Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.2023 · 233 citations
- Hurdles to Progress in Long-form Question AnsweringConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kalpesh Krishna, Aurko Roy, Mohit Iyyer2021 · 233 citations
- MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?Lecture notes in computer scienceRenrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.2024 · 232 citations
- GAIA: a benchmark for General AI AssistantsarXiv:2311.12983Gregoire Mialon, Clementine Fourrier, Craig Swift, et al.2023 · 232 citations
- Detecting Hallucinated Content in Conditional Neural Sequence GenerationFindings of the Association for Computational LinguisticsChunting Zhou, Graham Neubig, Jiatao Gu, et al.2021 · 232 citations
- ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot LearningarXiv:2304.06588Petter Tornberg2023 · 231 citations
- LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelarXiv:2304.15010Peng Gao, Jiaming Han, Renrui Zhang, et al.2023 · 229 citations
- Progress measures for grokking via mechanistic interpretabilityarXiv:2301.05217Neel Nanda, Lawrence Chan, Tom Lieberum, et al.2023 · 228 citations
- Self-critiquing models for assisting human evaluatorsarXiv:2206.05802William Saunders, Catherine Yeh, Jeff Wu, et al.2022 · 228 citations
- Qwen2.5-Omni Technical ReportarXiv:2503.20215Jin Xu, Zhifang Guo, Jinzheng He, et al.2025 · 227 citations
- MedAlpaca — An Open-Source Collection of Medical Conversational AI Models and Training DataarXiv:2304.08247Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, et al.2023 · 227 citations
- A Survey of Hallucination in Large Foundation ModelsarXiv:2309.05922Vipula Rawte, Amit Sheth, Amitava Das2023 · 226 citations
- DataComp: In search of the next generation of multimodal datasetsConference on Neural Information Processing Systems (NeurIPS)Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, et al.2023 · 224 citations
- Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought PromptingarXiv:2305.07004Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.2023 · 224 citations
- Reinforced Self-Training (ReST) for Language ModelingarXiv:2308.08998Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.2023 · 224 citations
- Specializing Smaller Language Models towards Multi-Step ReasoningarXiv:2301.12726Yao Fu, Hao Peng, Litu Ou, et al.2023 · 224 citations
- GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical InformationBioinformaticsQiao Jin, Yifan Yang, Qingyu Chen, et al.2023 · 223 citations
- Self-planning Code Generation with Large Language ModelsACM Transactions on Software Engineering and MethodologyXue Jiang, Yihong Dong, Lecheng Wang, et al.2023 · 223 citations
- Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
- Transformer Memory as a Differentiable Search IndexConference on Neural Information Processing Systems (NeurIPS)Yi Tay, Vinh Q. Tran, Mostafa Dehghani, et al.2022 · 223 citations
- NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding ModelsarXiv:2405.17428Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.2024 · 222 citations
- Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLParXiv:2212.14024Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.2022 · 222 citations
- Med-HALT: Medical Domain Hallucination Test for Large Language ModelsConference on Computational Natural Language Learning (CoNLL)Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu2023 · 221 citations
- Multilingual Translation from Denoising Pre-TrainingFindings of the Association for Computational LinguisticsYuqing Tang, Chau Tran, Xian Li, et al.2021 · 220 citations
- Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 219 citations
- Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical ReasoningarXiv:2209.14610Pan Lu, Liang Qiu, Kai-Wei Chang, et al.2022 · 219 citations
- FOLIO: Natural Language Reasoning with First-Order LogicarXiv:2209.00840Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.2022 · 219 citations
- Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language ModelsarXiv:2308.16149Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.2023 · 218 citations
- TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question AnsweringIEEE/CVF International Conference on Computer Vision (ICCV)Yushi Hu, Benlin Liu, Jungo Kasai, et al.2023 · 218 citations
- Teaching language models to support answers with verified quotesarXiv:2203.11147Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.2022 · 218 citations
- Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4arXiv:2304.03439Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.2023 · 217 citations
- Making Language Models Better Reasoners with Step-Aware VerifierAnnual Meeting of the Association for Computational Linguistics (ACL)Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.2023 · 217 citations
- Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 217 citations
- LLM+P: Empowering Large Language Models with Optimal Planning ProficiencyarXiv:2304.11477Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.2023 · 216 citations
- Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language ModelsFindings of the Association for Computational LinguisticsRobert Logan IV, Ivana Balazevic, Eric Wallace, et al.2022 · 216 citations
- MADLAD-400: A Multilingual And Document-Level Large Audited DatasetConference on Neural Information Processing Systems (NeurIPS)Sneha Kudugunta, Isaac Caswell, Biao Zhang, et al.2023 · 213 citations
- TinyStories: How Small Can Language Models Be and Still Speak Coherent English?Ronen Eldan, Yuanzhi Li2023 · 213 citations
- Demystifying Prompts in Language Models via Perplexity EstimationarXiv:2212.04037Hila Gonen, Srini Iyer, Terra Blevins, et al.2022 · 213 citations
- Challenges in Detoxifying Language ModelsFindings of the Association for Computational LinguisticsJohannes Welbl, Amelia Glaese, Jonathan Uesato, et al.2021 · 213 citations
- Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLParXiv:2103.00453Timo Schick, Sahana Udupa, Hinrich Schutze2021 · 213 citations
- Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine TranslationarXiv:2401.08417Haoran Xu, Amr Sharaf, Yunmo Chen, et al.2024 · 212 citations
- What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
- Compressing Context to Enhance Inference Efficiency of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Yucheng Li, Bo Dong, Frank Guerin, et al.2023 · 212 citations
- Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!Findings of the Association for Computational LinguisticsYubo Ma, Yixin Cao, Yong Hong, et al.2023 · 212 citations
- Ring Attention with Blockwise Transformers for Near-Infinite ContextarXiv:2310.01889Hao Liu, Matei Zaharia, Pieter Abbeel2023 · 212 citations
- Sources of Hallucination by Large Language Models on Inference TasksFindings of the Association for Computational LinguisticsNick McKenna, Tianyi Li, Liang Cheng, et al.2023 · 212 citations
- Language Models of Code are Few-Shot Commonsense LearnersConference on Empirical Methods in Natural Language Processing (EMNLP)Aman Madaan, Shuyan Zhou, Uri Alon, et al.2022 · 212 citations
- Scalable Extraction of Training Data from (Production) Language ModelsarXiv:2311.17035Milad Nasr, Nicholas Carlini, Jonathan Hayase, et al.2023 · 211 citations
- “Kelly is a Warm Person, Joseph is a Role Model”: Gender Biases in LLM-Generated Reference LettersFindings of the Association for Computational LinguisticsYixin Wan, George Pu, Jiao Sun, et al.2023 · 211 citations
- An Empirical Survey of the Effectiveness of Debiasing Techniques for Pre-trained Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Nicholas Meade, Elinor Poole-Dayan, Siva Reddy2022 · 211 citations
- Generating Training Data with Language Models: Towards Zero-Shot Language UnderstandingarXiv:2202.04538Yu Meng, Jiaxin Huang, Yu Zhang, et al.2022 · 210 citations
- Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
- CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Qinyuan Ye, Bill Yuchen Lin, Xiang Ren2021 · 210 citations
- SALMONN: Towards Generic Hearing Abilities for Large Language ModelsarXiv:2310.13289Changli Tang, Wenyi Yu, Guangzhi Sun, et al.2023 · 209 citations
- Active Example Selection for In-Context LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Yiming Zhang, Shi Feng, Chenhao Tan2022 · 209 citations
- Internet-augmented language models through few-shot prompting for open-domain question answeringarXiv:2203.05115Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, et al.2022 · 209 citations
- 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
- 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 · 208 citations
- Towards a Unified Multi-Dimensional Evaluator for Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Ming Zhong, Yang Liu, Da Yin, et al.2022 · 208 citations
- Recursively Summarizing Books with Human FeedbackarXiv:2109.10862Jeff Wu, Long Ouyang, Daniel M. Ziegler, et al.2021 · 208 citations
- Optimus: Organizing Sentences via Pre-trained Modeling of a Latent SpaceConference on Empirical Methods in Natural Language Processing (EMNLP)Chunyuan Li, Xiang Gao, Yuan Li, et al.2020 · 208 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 · 207 citations
- RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Cheng Niu, Yuanhao Wu, Juno Zhu, et al.2024 · 207 citations
- LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language ModelsarXiv:2305.13711Yen-Ting Lin, Yun-Nung Chen2023 · 207 citations
- BLINK: Multimodal Large Language Models Can See but Not PerceiveLecture notes in computer scienceXingyu Fu, Yushi Hu, Bangzheng Li, et al.2024 · 206 citations
- Woodpecker: Hallucination Correction for Multimodal Large Language ModelsScience China Information SciencesShukang Yin, Chaoyou Fu, Sirui Zhao, et al.2023 · 206 citations
- Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
- On the Effectiveness of Adapter-based Tuning for Pretrained Language Model AdaptationAnnual Meeting of the Association for Computational Linguistics (ACL)Ruidan He, Linlin Liu, Hai Ye, et al.2021 · 204 citations
- Measuring Multimodal Mathematical Reasoning with MATH-Vision DatasetConference on Neural Information Processing Systems (NeurIPS)Ke Wang, Junting Pan, Weikang Shi, et al.2024 · 203 citations
- DyLoRA: Parameter-Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank AdaptationConference of the European Chapter of the Association for Computational Linguistics (EACL)Mojtaba Valipour, Mehdi Rezagholizadeh, Ivan Kobyzev, et al.2023 · 203 citations
- mGPT: Few-Shot Learners Go MultilingualarXiv:2204.07580Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.2022 · 203 citations
- Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 202 citations
- Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasConference on Neural Information Processing Systems (NeurIPS)Yue Yu, Yuchen Zhuang, Jieyu Zhang, et al.2023 · 202 citations
- Model Tells You What to Discard: Adaptive KV Cache Compression for LLMsarXiv:2310.01801Suyu Ge, Yunan Zhang, Liyuan Liu, et al.2023 · 202 citations
- RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 201 citations
- CTRLsum: Towards Generic Controllable Text SummarizationConference on Empirical Methods in Natural Language Processing (EMNLP)Junxian He, Wojciech Kryscinski, Bryan McCann, et al.2022 · 201 citations
- ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree SearchConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.2024 · 200 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
- Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuningConference on Empirical Methods in Natural Language Processing (EMNLP)Runxin Xu, Fuli Luo, Zhiyuan Zhang, et al.2021 · 200 citations
- A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
- MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningarXiv:2310.09478Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.2023 · 199 citations
- Improving Passage Retrieval with Zero-Shot Question GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Devendra Sachan, Mike Lewis, Mandar Joshi, et al.2022 · 199 citations
- MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and TextConference on Empirical Methods in Natural Language Processing (EMNLP)Wenhu Chen, Hexiang Hu, Xi Chen, et al.2022 · 199 citations
- Position Information in Transformers: An OverviewComputational LinguisticsPhilipp Dufter, Martin Schmitt, Hinrich Schütze2022 · 198 citations
- OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text DocumentsConference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.2023 · 197 citations
- High-Fidelity Audio Compression with Improved RVQGANConference on Neural Information Processing Systems (NeurIPS)Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, et al.2023 · 196 citations
- MM-REACT: Prompting ChatGPT for Multimodal Reasoning and ActionarXiv:2303.11381Zhengyuan Yang, Linjie Li, Jianfeng Wang, et al.2023 · 196 citations
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