---
title: "Who cites Pierre Sermanet — page 2 — 1,745 citing papers"
description: "1,745 papers of the Elamur Research library cite the works of Pierre Sermanet, found in their bibliographies · page 2 of 3 · 101–200; the most…"
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---
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# Who cites Pierre Sermanet

2,013 citations of their works from 1,745 papers of our library (of the 149,439 whose bibliographies we read) · 277 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Pierre Sermanet](https://md.research.elamur.ai/free/en/authors/pierre-sermanet/)

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101. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
102. **[Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement](https://md.research.elamur.ai/free/en/papers/he-2016-pairwise-word-interaction-modeling-deep/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hua He, Jimmy Lin*2016 · 297 citations*
103. **[SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2018-switchout-efficient-data-augmentation-algorithm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xinyi Wang, Hieu Pham, Zihang Dai, et al.*2018 · 290 citations*
104. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
105. [**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/)
106. [**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/)
107. **[An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/chen-2024-image-worth-1-2-tokens/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Liang Chen, Haozhe Zhao, Tianyu Liu, et al.*2024 · 279 citations*
108. [**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/)
109. [**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/)
110. **[Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhou-2016-deep-recurrent-models-fast-forward/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jie Zhou, Ying Cao, Xuguang Wang, et al.*2016 · 265 citations*
111. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
112. **[DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 259 citations*
113. **[InternVideo2: Scaling Foundation Models for Multimodal Video Understanding](https://md.research.elamur.ai/free/en/papers/wang-2024-internvideo2-scaling-foundation-models/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yi Wang, Kunchang Li, Xinhao Li, et al.*2024 · 253 citations*
114. **[Language Models can Solve Computer Tasks](https://md.research.elamur.ai/free/en/papers/kim-2023-language-models-solve-computer-tasks/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Geunwoo Kim, Pierre Baldi, Stephen McAleer*2023 · 249 citations*
115. [**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/)
116. **[Visual Adversarial Examples Jailbreak Aligned Large Language Models](https://md.research.elamur.ai/free/en/papers/qi-2023-visual-adversarial-examples-jailbreak-aligned/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.*2023 · 240 citations*
117. **[Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/shen-2021-locate-label-two-stage-identifier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongliang Shen, Xinyin Ma, Zeqi Tan, et al.*2021 · 232 citations*
118. [**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/)
119. **[Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models](https://md.research.elamur.ai/free/en/papers/li-2023-monkey-image-resolution-text-label/) [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/)**Zhang Li, Biao Yang, Qiang Liu, et al.*2023 · 222 citations*
120. **[PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change](https://md.research.elamur.ai/free/en/papers/valmeekam-2022-planbench-extensible-benchmark-evaluating-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.*2022 · 222 citations*
121. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents arXiv:2407.16741**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 221 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
122. **[Few-Shot Charge Prediction with Discriminative Legal Attributes](https://md.research.elamur.ai/free/en/papers/hu-2018-few-shot-charge-prediction-discriminative/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zikun Hu, Xiang Li, Cunchao Tu, et al.*2018 · 221 citations*
123. [**AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors arXiv:2308.10848**Weize Chen, Yusheng Su, Jingwei Zuo, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-agentverse-facilitating-multi-agent/)
124. **[RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback](https://md.research.elamur.ai/free/en/papers/yu-2023-rlhf-v-towards-trustworthy-mllms/) [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/)**Tianyu Yu, Yuan Yao, Haoye Zhang, et al.*2023 · 217 citations*
125. [**LLM+P: Empowering Large Language Models with Optimal Planning Proficiency arXiv:2304.11477**Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.*2023 · 216 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-llm-p-empowering-large-language/)
126. **[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*
127. [**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/)
128. [**A Convolutional Attention Network for Extreme Summarization of Source Code arXiv:1602.03001**Miltiadis Allamanis, Hao Peng, Charles Sutton*2016 · 198 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/)
129. [**MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action arXiv:2303.11381**Zhengyuan Yang, Linjie Li, Jianfeng Wang, et al.*2023 · 196 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-mm-react-prompting-chatgpt-multimodal/)
130. **[InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/zhan-2024-injecagent-benchmarking-indirect-prompt-injections/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiusi Zhan, Zhixiang Liang, Zifan Ying, et al.*2024 · 193 citations*
131. [**What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation arXiv:2008.03703**Vitaly Feldman, Chiyuan Zhang*2020 · 193 citations*](https://md.research.elamur.ai/free/en/papers/feldman-2020-neural-networks-memorize-why-discovering/)
132. **[On the Planning Abilities of Large Language Models : A Critical Investigation](https://md.research.elamur.ai/free/en/papers/valmeekam-2023-planning-abilities-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan, et al.*2023 · 191 citations*
133. **[Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces](https://md.research.elamur.ai/free/en/papers/yang-2024-thinking-space-multimodal-large-language/) [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/)**Jihan Yang, Shusheng Yang, Anjali W. Gupta, et al.*2024 · 182 citations*
134. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
135. [**Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads arXiv:1901.05758**Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, et al.*2019 · 179 citations*](https://md.research.elamur.ai/free/en/papers/jeon-2019-analysis-large-scale-multi-tenant/)
136. [**Aligning Large Multimodal Models with Factually Augmented RLHF arXiv:2309.14525**Zhiqing Sun, Sheng Shen, Shengcao Cao, et al.*2023 · 176 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-aligning-large-multimodal-models-factually/)
137. [**Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents arXiv:2302.01560**Zihao Wang, Shaofei Cai, Guanzhou Chen, et al.*2023 · 174 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-describe-explain-plan-select-interactive/)
138. [**Capabilities of Gemini Models in Medicine arXiv:2404.18416**Khaled Saab, Tao Tu, Wei-Hung Weng, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/saab-2024-capabilities-gemini-models-medicine/)
139. [**Executable Code Actions Elicit Better LLM Agents arXiv:2402.01030**Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-executable-code-actions-elicit-better/)
140. [**CLIPort: What and Where Pathways for Robotic Manipulation arXiv:2109.12098**Mohit Shridhar, Lucas Manuelli, Dieter Fox*2021 · 159 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2021-cliport-where-pathways-robotic-manipulation/)
141. **[Large Language Models as Commonsense Knowledge for Large-Scale Task Planning](https://md.research.elamur.ai/free/en/papers/zhao-2023-large-language-models-commonsense-knowledge/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zirui Zhao, Wee Sun Lee, David Hsu*2023 · 153 citations*
142. [**MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge arXiv:2206.08853**Linxi Fan, Guanzhi Wang, Yunfan Jiang, et al.*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/fan-2022-minedojo-building-open-ended-embodied/)
143. [**TALM: Tool Augmented Language Models arXiv:2205.12255**Aaron Parisi, Yao Zhao, Noah Fiedel*2022 · 149 citations*](https://md.research.elamur.ai/free/en/papers/parisi-2022-talm-tool-augmented-language-models/)
144. **[GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction](https://md.research.elamur.ai/free/en/papers/yang-2023-gpt4tools-teaching-large-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rui Yang, Lin Song, Yanwei Li, et al.*2023 · 147 citations*
145. **[ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings](https://md.research.elamur.ai/free/en/papers/hao-2023-toolkengpt-augmenting-frozen-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shibo Hao, Tianyang Liu, Zhen Wang, et al.*2023 · 147 citations*
146. [**Efficient Processing of Deep Neural Networks: A Tutorial and Survey Proceedings of the IEEE 2017**Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, et al.*2017 · 146 citations*](https://md.research.elamur.ai/free/en/papers/sze-2017-efficient-processing-deep-neural-networks/)
147. [**PaliGemma: A versatile 3B VLM for transfer arXiv:2407.07726**Lucas Beyer, Andreas Steiner, Andre Susano Pinto, et al.*2024 · 142 citations*](https://md.research.elamur.ai/free/en/papers/beyer-2024-paligemma-versatile-3b-vlm-transfer/)
148. [**Eureka: Human-Level Reward Design via Coding Large Language Models arXiv:2310.12931**Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-eureka-human-level-reward-design/)
149. **[Deep Network Guided Proof Search](https://md.research.elamur.ai/free/en/papers/loos-2017-deep-network-guided-proof-search/) [EPiC series in computing](https://md.research.elamur.ai/free/en/venues/epic-series-in-computing/)**Sarah Loos, Geoffrey Irving, Christian Szegedy, et al.*2017 · 139 citations*
150. **[Theory of Mind for Multi-Agent Collaboration via Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-theory-mind-multi-agent-collaboration/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Huao Li, Yu Chong, Simon Stepputtis, et al.*2023 · 138 citations*
151. [**τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains arXiv:2406.12045**Shunyu Yao, Noah Shinn, Pedram Razavi, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-tau-bench-benchmark-tool/)
152. [**Secrets of RLHF in Large Language Models Part I: PPO arXiv:2307.04964**Rui Zheng, Shihan Dou, Songyang Gao, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-secrets-rlhf-large-language-models/)
153. **[Deductive Verification of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 130 citations*
154. **[InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory](https://md.research.elamur.ai/free/en/papers/xiao-2024-infllm-training-free-long-context/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaojun Xiao, Pengle Zhang, Xu Han, et al.*2024 · 126 citations*
155. [**TravelPlanner: A Benchmark for Real-World Planning with Language Agents arXiv:2402.01622**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-travelplanner-benchmark-real-world-planning/)
156. [**FAST: Efficient Action Tokenization for Vision-Language-Action Models arXiv:2501.09747**Karl Pertsch, Kyle Stachowicz, Brian Ichter, et al.*2025 · 123 citations*](https://md.research.elamur.ai/free/en/papers/pertsch-2025-fast-efficient-action-tokenization-vision/)
157. **[Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages](https://md.research.elamur.ai/free/en/papers/qin-2023-cross-lingual-prompting-improving-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Libo Qin, Qiguang Chen, Fuxuan Wei, et al.*2023 · 122 citations*
158. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
159. [**A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis arXiv:2307.12856**Izzeddin Gur, Hiroki Furuta, Austin Huang, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/gur-2023-real-world-webagent-planning-long/)
160. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
161. **[Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning](https://md.research.elamur.ai/free/en/papers/guan-2023-leveraging-pre-trained-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lin Guan, Karthik Valmeekam, Sarath Sreedharan, et al.*2023 · 115 citations*
162. **[Generalized Planning in PDDL Domains with Pretrained Large Language Models](https://md.research.elamur.ai/free/en/papers/silver-2023-generalized-planning-pddl-domains-pretrained/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Tom Silver, Soham Dan, Kavitha Srinivas, et al.*2023 · 112 citations*
163. **[SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks](https://md.research.elamur.ai/free/en/papers/lin-2023-swiftsage-generative-agent-fast-slow/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bill Yuchen Lin, Yicheng Fu, Karina Yang, et al.*2023 · 110 citations*
164. [**PaperQA: Retrieval-Augmented Generative Agent for Scientific Research arXiv:2312.07559**Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/lala-2023-paperqa-retrieval-augmented-generative/)
165. [**Prompt Cache: Modular Attention Reuse for Low-Latency Inference MLSys 2024**In Gim, Guojun Chen, Seung-seob Lee, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/gim-2023-prompt-cache-modular-attention-reuse/)
166. [**AppAgent: Multimodal Agents as Smartphone Users arXiv:2312.13771**Chi Zhang, Zhao Yang, Jiaxuan Liu, et al.*2023 · 107 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-appagent-multimodal-agents-smartphone-users/)
167. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
168. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
169. [**FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets arXiv:2307.10928**Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.*2023 · 100 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-flask-fine-grained-language-model/)
170. [**Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango arXiv:2209.07686**Aman Madaan, Amir Yazdanbakhsh*2022 · 98 citations*](https://md.research.elamur.ai/free/en/papers/madaan-2022-text-patterns-effective-chain-thought/)
171. [**Accelerating Sparse Deep Neural Networks arXiv 2021 (NVIDIA)**Asit Mishra, Jorge Albericio Latorre, Jeff Pool, et al.*2021 · 97 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2021-accelerating-sparse-deep-neural-networks/)
172. [**The Platonic Representation Hypothesis arXiv:2405.07987**Minyoung Huh, Brian Cheung, Tongzhou Wang, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/huh-2024-platonic-representation-hypothesis/)
173. [**Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory arXiv:2305.17144**Xizhou Zhu, Yuntao Chen, Hao Tian, et al.*2023 · 96 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-ghost-minecraft-generally-capable-agents/)
174. [**Identifying the Risks of LM Agents with an LM-Emulated Sandbox arXiv:2309.15817**Yangjun Ruan, Honghua Dong, Andrew Wang, et al.*2023 · 96 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2023-identifying-risks-lm-agents-lm/)
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