Who cites Aida Nematzadeh
- HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianrui Guan, Fuxiao Liu, Xiyang Wu, et al.2023 · 335 citations
- LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init AttentionarXiv:2303.16199Renrui Zhang, Jiaming Han, Chris Liu, et al.2023 · 333 citations
- Language Is Not All You Need: Aligning Perception with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Shaohan Huang, Li Dong, Wenhui Wang, et al.2023 · 330 citations
- Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation ModelsarXiv:2303.04671Chenfei Wu, Shengming Yin, Weizhen Qi, et al.2023 · 328 citations
- Faith and Fate: Limits of Transformers on CompositionalityConference on Neural Information Processing Systems (NeurIPS)Nouha Dziri, Ximing Lu, Melanie Sclar, et al.2023 · 327 citations
- Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive DecodingIEEE Computer Society Conference on Computer Vision and Pattern RecognitionSicong Leng, Hang Zhang, Guanzheng Chen, et al.2023 · 322 citations
- Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionShengbang Tong, Zhuang Liu, Yuexiang Zhai, et al.2024 · 321 citations
- MM-LLMs: Recent Advances in MultiModal Large Language ModelsFindings of the Association for Computational LinguisticsDuzhen Zhang, Yahan Yu, Jiahua Dong, et al.2024 · 320 citations
- GIT: A Generative Image-to-text Transformer for Vision and LanguagearXiv:2205.14100Jianfeng Wang, Zhengyuan Yang, Xiaowei Hu, et al.2022 · 319 citations
- The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)arXiv:2309.17421Zhengyuan Yang, Linjie Li, Kevin Lin, et al.2023 · 311 citations
- Social Simulacra: Creating Populated Prototypes for Social Computing SystemsarXiv:2208.04024Joon Sung Park, Lindsay Popowski, Carrie J. Cai, et al.2022 · 310 citations
- Multimodal Chain-of-Thought Reasoning in Language ModelsarXiv:2302.00923Zhuosheng Zhang, Aston Zhang, Mu Li, et al.2023 · 308 citations
- OCRBench: On the Hidden Mystery of OCR in Large Multimodal ModelsScience China Information SciencesYuliang Liu, Zhang Li, Mingxin Huang, et al.2023 · 306 citations
- Large Language Models are Better Reasoners with Self-VerificationFindings of the Association for Computational LinguisticsYixuan Weng, Minjun Zhu, Fei Xia, et al.2023 · 304 citations
- InternLM2 Technical ReportarXiv:2403.17297Zheng Cai, Maosong Cao, Haojiong Chen, et al.2024 · 301 citations
- Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
- xLSTM: Extended Long Short-Term MemoryConference on Neural Information Processing Systems (NeurIPS)Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.2024 · 296 citations
- Can language models learn from explanations in context?Findings of the Association for Computational LinguisticsAndrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.2022 · 295 citations
- Text Classification via Large Language ModelsFindings of the Association for Computational LinguisticsXiaofei Sun, Xiaoya Li, Jiwei Li, et al.2023 · 292 citations
- Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
- Kosmos-2: Grounding Multimodal Large Language Models to the WorldarXiv:2306.14824Zhiliang Peng, Wenhui Wang, Li Dong, et al.2023 · 286 citations
- Generate rather than Retrieve: Large Language Models are Strong Context GeneratorsarXiv:2209.10063Wenhao Yu, Dan Iter, Shuohang Wang, et al.2022 · 281 citations
- Towards Measuring the Representation of Subjective Global Opinions in Language ModelsarXiv:2306.16388Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 270 citations
- MiniCPM-V: A GPT-4V Level MLLM on Your PhonearXiv:2408.01800Yuan Yao, Tianyu Yu, Ao Zhang, et al.2024 · 269 citations
- MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
- Predictability and Surprise in Large Generative ModelsACM Conference on Fairness, Accountability, and Transparency (FAccT)Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.2022 · 268 citations
- LLaMA-VID: An Image is Worth 2 Tokens in Large Language ModelsLecture notes in computer scienceYanwei Li, Chengyao Wang, Jiaya Jia2023 · 262 citations
- RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 260 citations
- SocialIQA: Commonsense Reasoning about Social InteractionsarXiv:1904.09728Maarten Sap, Hannah Rashkin, Derek Chen, et al.2019 · 259 citations
- Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
- InternVideo2: Scaling Foundation Models for Multimodal Video UnderstandingLecture notes in computer scienceYi Wang, Kunchang Li, Xinhao Li, et al.2024 · 253 citations
- Language Models can Solve Computer TasksConference on Neural Information Processing Systems (NeurIPS)Geunwoo Kim, Pierre Baldi, Stephen McAleer2023 · 249 citations
- Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and ToxicityarXiv:2301.12867Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.2023 · 249 citations
- BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagearXiv:2208.03188Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.2022 · 241 citations
- Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
- Visual Adversarial Examples Jailbreak Aligned Large Language ModelsProceedings of the AAAI Conference on Artificial IntelligenceXiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.2023 · 240 citations
- Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video UnderstandingarXiv:2306.02858Hang Zhang, Xin Li, Lidong Bing2023 · 238 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
- 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
- LLaMA-Adapter V2: Parameter-Efficient Visual Instruction ModelarXiv:2304.15010Peng Gao, Jiaming Han, Renrui Zhang, et al.2023 · 229 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
- Reinforced Self-Training (ReST) for Language ModelingarXiv:2308.08998Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.2023 · 224 citations
- Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionZhang Li, Biao Yang, Qiang Liu, et al.2023 · 222 citations
- OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language ModelsarXiv:2308.01390Anas Awadalla, Irena Gao, Josh Gardner, et al.2023 · 222 citations
- PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeConference on Neural Information Processing Systems (NeurIPS)Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.2022 · 222 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
- Teaching language models to support answers with verified quotesarXiv:2203.11147Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.2022 · 218 citations
- RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human FeedbackIEEE Computer Society Conference on Computer Vision and Pattern RecognitionTianyu Yu, Yuan Yao, Haoye Zhang, et al.2023 · 217 citations
- Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
- Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 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
- Shikra: Unleashing Multimodal LLM's Referential Dialogue MagicarXiv:2306.15195Keqin Chen, Zhao Zhang, Weili Zeng, et al.2023 · 210 citations
- Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 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
- Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 208 citations
- NExT-GPT: Any-to-Any Multimodal LLMarXiv:2309.05519Shengqiong Wu, Hao Fei, Leigang Qu, et al.2023 · 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
- RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 201 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
- 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
- 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
- MM-REACT: Prompting ChatGPT for Multimodal Reasoning and ActionarXiv:2303.11381Zhengyuan Yang, Linjie Li, Jianfeng Wang, et al.2023 · 196 citations
- Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human FeedbackConference on Empirical Methods in Natural Language Processing (EMNLP)Viet Lai, Chien Nguyen, Nghia Ngo, et al.2023 · 195 citations
- RAPTOR: Recursive Abstractive Processing for Tree-Organized RetrievalarXiv:2401.18059Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.2024 · 193 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 · 191 citations
- Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.2022 · 190 citations
- Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction TuningarXiv:2306.14565Fuxiao Liu, Kevin Lin, Linjie Li, et al.2023 · 189 citations
- SGPT: GPT Sentence Embeddings for Semantic SearcharXiv:2202.08904Niklas Muennighoff2022 · 189 citations
- VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Jing Yu Koh, Robert Lo, Lawrence Jang, et al.2024 · 184 citations
- Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language ModelsarXiv:2311.07919Yunfei Chu, Jin Xu, Xiaohuan Zhou, et al.2023 · 184 citations
- 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
- Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall SpacesIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJihan Yang, Shusheng Yang, Anjali W. Gupta, et al.2024 · 182 citations
- Large Language Models are few(1)-shot Table ReasonersFindings of the Association for Computational LinguisticsWenhu Chen2023 · 182 citations
- CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 LanguagesLanguage Resources and Evaluation Conference (LREC)Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.2023 · 181 citations
- What Artificial Neural Networks Can Tell Us About Human Language AcquisitionarXiv:2208.07998Alex Warstadt, Samuel R. Bowman2022 · 177 citations
- Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task AgentsarXiv:2302.01560Zihao Wang, Shaofei Cai, Guanzhou Chen, et al.2023 · 174 citations
- Do All Languages Cost the Same? Tokenization in the Era of Commercial Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.2023 · 174 citations
- Generative Representational Instruction TuningarXiv:2402.09906Niklas Muennighoff, Hongjin Su, Liang Wang, et al.2024 · 172 citations
- AudioPaLM: A Large Language Model That Can Speak and ListenarXiv:2306.12925Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen, et al.2023 · 171 citations
- Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
- Capabilities of Gemini Models in MedicinearXiv:2404.18416Khaled Saab, Tao Tu, Wei-Hung Weng, et al.2024 · 170 citations
- Quark: Controllable Text Generation with Reinforced UnlearningConference on Neural Information Processing Systems (NeurIPS)Ximing Lu, Sean Welleck, Jack Hessel, et al.2022 · 170 citations
- Factuality Enhanced Language Models for Open-Ended Text GenerationConference on Neural Information Processing Systems (NeurIPS)Nayeon Lee, Wei Ping, Peng Xu, et al.2022 · 168 citations
- “I'm sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor DatasetConference on Empirical Methods in Natural Language Processing (EMNLP)Eric Michael Smith, Melissa Hall, Melanie Kambadur, et al.2022 · 167 citations
- Language models show human-like content effects on reasoning tasksarXiv:2207.07051Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, et al.2022 · 162 citations
- Chameleon: Mixed-Modal Early-Fusion Foundation ModelsarXiv:2405.09818Chameleon Team2024 · 159 citations
- Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and OrderingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyong Wu, Yaoxiang Wang, Jiacheng Ye, et al.2022 · 159 citations
- Large Language Models with Controllable Working MemoryFindings of the Association for Computational LinguisticsDaliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.2023 · 158 citations
- TheoremQA: A Theorem-driven Question Answering DatasetConference on Empirical Methods in Natural Language Processing (EMNLP)Wenhu Chen, Ming Yin, Max Ku, et al.2023 · 158 citations
- Are aligned neural networks adversarially aligned?Conference on Neural Information Processing Systems (NeurIPS)Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.2023 · 157 citations
- Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
- Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
- AnnoLLM: Making Large Language Models to Be Better Crowdsourced AnnotatorsarXiv:2303.16854Xingwei He, Zhenghao Lin, Yeyun Gong, et al.2023 · 152 citations
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