---
title: "Who cites Li-Jia Li — page 2 — 3,365 papers of our library"
description: "3,365 papers of the Elamur Research library cite the works of Li-Jia Li, found in their bibliographies · page 2 of 3 · 101–200; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/li-jia-li/cited-by/page/2/"
---
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# Who cites Li-Jia Li

3,694 citations of their works from 3,365 papers of our library (of the 149,439 whose bibliographies we read) · 292 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Li-Jia Li](https://md.research.elamur.ai/free/en/authors/li-jia-li/)

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101. [**SimVLM: Simple Visual Language Model Pretraining with Weak Supervision arXiv:2108.10904**Zirui Wang, Jiahui Yu, Adams Wei Yu, et al.*2021 · 481 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-simvlm-simple-visual-language-model/)
102. **[HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training](https://md.research.elamur.ai/free/en/papers/li-2020-hero-hierarchical-encoder-video-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Linjie Li, Yen-Chun Chen, Yu Cheng, et al.*2020 · 481 citations*
103. [**ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware arXiv:1812.00332**Han Cai, Ligeng Zhu, Song Han*2018 · 479 citations*](https://md.research.elamur.ai/free/en/papers/cai-2018-proxylessnas-direct-neural-architecture-search/)
104. [**LLaVA-OneVision: Easy Visual Task Transfer arXiv:2408.03326**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 477 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
105. [**Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection arXiv:2303.05499**Shilong Liu, Zhaoyang Zeng, Tianhe Ren, et al.*2023 · 472 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-grounding-dino-marrying-dino-grounded/)
106. [**CogView: Mastering Text-to-Image Generation via Transformers arXiv:2105.13290**Ming Ding, Zhuoyi Yang, Wenyi Hong, et al.*2021 · 469 citations*](https://md.research.elamur.ai/free/en/papers/ding-2021-cogview-mastering-text-image/)
107. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework arXiv:2202.03052**Peng Wang, An Yang, Rui Men, et al.*2022 · 467 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
108. [**CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning arXiv:1612.06890**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2016 · 464 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2016-clevr-diagnostic-dataset-compositional-language/)
109. **[MVBench: A Comprehensive Multi-modal Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 463 citations*
110. **[ShareGPT4V: Improving Large Multi-Modal Models with Better Captions](https://md.research.elamur.ai/free/en/papers/chen-2023-sharegpt4v-improving-large-multi-modal/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2023 · 454 citations*
111. **[OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/moon-2019-opendialkg-explainable-conversational-reasoning-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungwhan Moon, Pararth Shah, Anuj Kumar, et al.*2019 · 449 citations*
112. **[Experience Grounds Language](https://md.research.elamur.ai/free/en/papers/bisk-2020-experience-grounds-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.*2020 · 439 citations*
113. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks arXiv:2312.14238**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 435 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
114. [**Benchmarking Neural Network Robustness to Common Corruptions and Perturbations arXiv:1903.12261**Dan Hendrycks, Thomas Dietterich*2019 · 434 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2019-benchmarking-neural-network-robustness-common/)
115. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes arXiv:2005.04790**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
116. [**Deep Learning: A Critical Appraisal arXiv:1801.00631**Gary Marcus*2018 · 417 citations*](https://md.research.elamur.ai/free/en/papers/marcus-2018-deep-learning-critical-appraisal/)
117. [**Yi: Open Foundation Models by 01.AI arXiv:2403.04652**Alex Young, Bei Chen, Chao Li, et al.*2024 · 408 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
118. **[ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2019-activitynet-qa-dataset-understanding-complex/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Zhou Yu, Dejing Xu, Jun Yu, et al.*2019 · 403 citations*
119. [**Editing Models with Task Arithmetic arXiv:2212.04089**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
120. [**Green AI arXiv:1907.10597**Roy Schwartz, Jesse Dodge, Noah A. Smith, et al.*2019 · 389 citations*](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/)
121. **[CogVLM: Visual Expert for Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-cogvlm-visual-expert-pretrained/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.*2023 · 383 citations*
122. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model arXiv:2209.06794**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 371 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/)
123. **[Combining Language and Vision with a Multimodal Skip-gram Model](https://md.research.elamur.ai/free/en/papers/lazaridou-2015-combining-language-vision-multimodal-skip/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Angeliki Lazaridou, Nghia The Pham, Marco Baroni*2015 · 368 citations*
124. **[VideoChat: Chat-Centric Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2023-videochat-chat-centric-video-understanding/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**KunChang Li, Yinan He, Yi Wang, et al.*2023 · 365 citations*
125. **[Visual Storytelling](https://md.research.elamur.ai/free/en/papers/huang-2016-visual-storytelling/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ting-Hao Kenneth Huang, Francis Ferraro, Nasrin Mostafazadeh, et al.*2016 · 356 citations*
126. [**Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes arXiv:1807.11205**Xianyan Jia, Shutao Song, Wei He, et al.*2018 · 348 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-highly-scalable-deep-learning-training/)
127. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
128. **[Improving Multimodal Named Entity Recognition via Entity Span Detection with Unified Multimodal Transformer](https://md.research.elamur.ai/free/en/papers/yu-2020-improving-multimodal-named-entity-recognition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianfei Yu, Jing Jiang, Li Yang, et al.*2020 · 342 citations*
129. [**LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention arXiv:2303.16199**Renrui Zhang, Jiaming Han, Chris Liu, et al.*2023 · 333 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llama-adapter-efficient-fine-tuning/)
130. **[Language Is Not All You Need: Aligning Perception with Language Models](https://md.research.elamur.ai/free/en/papers/huang-2023-language-all-need-aligning-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shaohan Huang, Li Dong, Wenhui Wang, et al.*2023 · 330 citations*
131. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
132. **[Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)](https://md.research.elamur.ai/free/en/papers/castro-2019-towards-multimodal-sarcasm-detection-obviously/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 320 citations*
133. **[WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning](https://md.research.elamur.ai/free/en/papers/srinivasan-2021-wit-wikipedia-based-image-text/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Krishna Srinivasan, Karthik Raman, Jiecao Chen, et al.*2021 · 315 citations*
134. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
135. **[UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning](https://md.research.elamur.ai/free/en/papers/li-2021-unimo-unified-modal-understanding-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Li, Can Gao, Guocheng Niu, et al.*2021 · 308 citations*
136. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language arXiv:2204.00598**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
137. **[CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/le-2022-coderl-mastering-code-generation-through/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.*2022 · 297 citations*
138. **[HAT: Hardware-Aware Transformers for Efficient Natural Language Processing](https://md.research.elamur.ai/free/en/papers/wang-2020-hat-hardware-aware-transformers-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanrui Wang, Zhanghao Wu, Zhijian Liu, et al.*2020 · 294 citations*
139. **[Detecting Sarcasm in Multimodal Social Platforms](https://md.research.elamur.ai/free/en/papers/schifanella-2016-detecting-sarcasm-multimodal-social-platforms/) [ACM International Conference on Multimedia (ACM MM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-multimedia-acm-mm/)**Rossano Schifanella, Paloma de Juan, Joel Tetreault, et al.*2016 · 290 citations*
140. [**SPICE: Semantic Propositional Image Caption Evaluation arXiv:1607.08822**Peter Anderson, Basura Fernando, Mark Johnson, et al.*2016 · 289 citations*](https://md.research.elamur.ai/free/en/papers/anderson-2016-spice-semantic-propositional-image-caption/)
141. **[Learning Grounded Meaning Representations with Autoencoders](https://md.research.elamur.ai/free/en/papers/silberer-2014-learning-grounded-meaning-representations-autoencoders/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Carina Silberer, Mirella Lapata*2014 · 288 citations*
142. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 287 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
143. [**Kosmos-2: Grounding Multimodal Large Language Models to the World arXiv:2306.14824**Zhiliang Peng, Wenhui Wang, Li Dong, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-kosmos-2-grounding-multimodal-large/)
144. [**Beyond Data and Model Parallelism for Deep Neural Networks SysML 2019**Zhihao Jia, Matei Zaharia, Alex Aiken*2018 · 280 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/)
145. [**Scaling Laws for Autoregressive Generative Modeling arXiv:2010.14701**Tom Henighan, Jared Kaplan, Mor Katz, et al.*2020 · 277 citations*](https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/)
146. **[Hubness and Pollution: Delving into Cross-Space Mapping for Zero-Shot Learning](https://md.research.elamur.ai/free/en/papers/lazaridou-2015-hubness-pollution-delving-into-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Angeliki Lazaridou, Georgiana Dinu, Marco Baroni*2015 · 276 citations*
147. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
148. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone arXiv:2408.01800**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
149. [**Perceiver: General Perception with Iterative Attention arXiv:2103.03206**Andrew Jaegle, Felix Gimeno, Andrew Brock, et al.*2021 · 269 citations*](https://md.research.elamur.ai/free/en/papers/jaegle-2021-perceiver-general-perception-iterative-attention/)
150. **[LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-llama-vid-image-worth-2/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yanwei Li, Chengyao Wang, Jiaya Jia*2023 · 262 citations*
151. **[SemEval-2020 Task 8: Memotion Analysis- the Visuo-Lingual Metaphor!](https://md.research.elamur.ai/free/en/papers/sharma-2020-semeval-2020-task-8-memotion/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Chhavi Sharma, Deepesh Bhageria, William Scott, et al.*2020 · 261 citations*
152. [**Multimodal Few-Shot Learning with Frozen Language Models arXiv:2106.13884**Maria Tsimpoukelli, Jacob Menick, Serkan Cabi, et al.*2021 · 258 citations*](https://md.research.elamur.ai/free/en/papers/tsimpoukelli-2021-multimodal-few-shot-learning-frozen/)
153. [**MiniF2F: a cross-system benchmark for formal Olympiad-level mathematics arXiv:2109.00110**Kunhao Zheng, Jesse Michael Han, Stanislas Polu*2021 · 257 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2021-minif2f-cross-system-benchmark-formal/)
154. [**Once-for-All: Train One Network and Specialize it for Efficient Deployment arXiv:1908.09791**Han Cai, Chuang Gan, Tianzhe Wang, et al.*2019 · 252 citations*](https://md.research.elamur.ai/free/en/papers/cai-2019-once-all-train-one-network/)
155. [**Long-term Recurrent Convolutional Networks for Visual Recognition and Description arXiv:1411.4389**Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, et al.*2014 · 245 citations*](https://md.research.elamur.ai/free/en/papers/donahue-2014-long-term-recurrent-convolutional-networks/)
156. [**The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision arXiv:1904.12584**Jiayuan Mao, Chuang Gan, Pushmeet Kohli, et al.*2019 · 241 citations*](https://md.research.elamur.ai/free/en/papers/mao-2019-neuro-symbolic-concept-learner-interpreting/)
157. **[OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation](https://md.research.elamur.ai/free/en/papers/huang-2023-opera-alleviating-hallucination-multi-modal/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Qidong Huang, Xiaoyi Dong, Pan Zhang, et al.*2023 · 238 citations*
158. [**LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model arXiv:2304.15010**Peng Gao, Jiaming Han, Renrui Zhang, et al.*2023 · 229 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-llama-adapter-v2-parameter-efficient/)
159. [**Overview of the TREC 2019 deep learning track arXiv:2003.07820**Nick Craswell, Bhaskar Mitra, Emine Yilmaz, et al.*2020 · 228 citations*](https://md.research.elamur.ai/free/en/papers/craswell-2020-overview-trec-2019-deep-learning/)
160. **[Towards Multimodal Sarcasm Detection (An \textitObviously Perfect Paper)](https://md.research.elamur.ai/free/en/papers/castro-2019-multimodal-sarcasm-detection-textitobviously-perfect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 228 citations*
161. **[DataComp: In search of the next generation of multimodal datasets](https://md.research.elamur.ai/free/en/papers/gadre-2023-datacomp-search-next-generation-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, et al.*2023 · 224 citations*
162. [**Estimating Training Data Influence by Tracing Gradient Descent arXiv:2002.08484**Garima Pruthi, Frederick Liu, Mukund Sundararajan, et al.*2020 · 223 citations*](https://md.research.elamur.ai/free/en/papers/pruthi-2020-estimating-training-data-influence-tracing/)
163. **[Probing the Need for Visual Context in Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/caglayan-2019-probing-need-visual-context-multimodal/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ozan Caglayan, Pranava Madhyastha, Lucia Specia, et al.*2019 · 217 citations*
164. **[Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 216 citations*
165. **[What matters when building vision-language models?](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 212 citations*
166. [**Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic arXiv:2306.15195**Keqin Chen, Zhao Zhang, Weili Zeng, et al.*2023 · 210 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-shikra-unleashing-multimodal-llm-s/)
167. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
168. **[Merging Models with Fisher-Weighted Averaging](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Matena, Colin Raffel*2021 · 208 citations*
169. **[BLINK: Multimodal Large Language Models Can See but Not Perceive](https://md.research.elamur.ai/free/en/papers/fu-2024-blink-multimodal-large-language-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xingyu Fu, Yushi Hu, Bangzheng Li, et al.*2024 · 206 citations*
170. [**Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning arXiv:2306.14565**Fuxiao Liu, Kevin Lin, Linjie Li, et al.*2023 · 189 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mitigating-hallucination-large-multi-modal/)
171. [**8-bit Optimizers via Block-wise Quantization arXiv:2110.02861**Tim Dettmers, Mike Lewis, Sam Shleifer, et al.*2021 · 181 citations*](https://md.research.elamur.ai/free/en/papers/dettmers-2021-8-bit-optimizers-block-wise/)
172. [**Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs arXiv:2210.12283**Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.*2022 · 178 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-draft-sketch-prove-guiding-formal/)
173. [**What Artificial Neural Networks Can Tell Us About Human Language Acquisition arXiv:2208.07998**Alex Warstadt, Samuel R. Bowman*2022 · 177 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2022-artificial-neural-networks-tell-us/)
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