---
title: "Who cites Trevor Jackson — page 2 — 5,295 citing papers"
description: "5,295 papers of the Elamur Research library cite the works of Trevor Jackson Darrell, found in their bibliographies · page 2 of 5 · 101–200…"
canonical: "https://research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Trevor Jackson Darrell](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/) / [cited by](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/) / page 2

# Who cites Trevor Jackson Darrell

7,658 citations of their works from 5,295 papers of our library (of the 149,439 whose bibliographies we read) · 445 with a page here, the most cited first · page 2 of 5 · 101–200 · [← Trevor Jackson Darrell](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/)

[← prev](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/3/) [4](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/4/) [5](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/5/) [next →](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/3/)

101. [**RL²: Fast Reinforcement Learning via Slow Reinforcement Learning arXiv:1611.02779**Yan Duan, John Schulman, Xi Chen, et al.*2016 · 524 citations*](https://md.research.elamur.ai/free/en/papers/duan-2016-rl-2-fast-reinforcement-learning/)
102. [**Learned in Translation: Contextualized Word Vectors arXiv:1708.00107**Bryan McCann, James Bradbury, Caiming Xiong, et al.*2017 · 512 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2017-learned-translation-contextualized-word-vectors/)
103. **[A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge](https://md.research.elamur.ai/free/en/papers/schwenk-2022-okvqa-benchmark-visual-question-answering/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Dustin Schwenk, Apoorv Khandelwal, Christopher Clark, et al.*2022 · 509 citations*
104. [**Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time arXiv:2203.05482**Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.*2022 · 507 citations*](https://md.research.elamur.ai/free/en/papers/wortsman-2022-model-soups-averaging-weights-multiple/)
105. [**DyNet: The Dynamic Neural Network Toolkit arXiv:1701.03980**Graham Neubig, Chris Dyer, Yoav Goldberg, et al.*2017 · 489 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2017-dynet-dynamic-neural-network-toolkit/)
106. **[On the Automatic Generation of Medical Imaging Reports](https://md.research.elamur.ai/free/en/papers/jing-2018-automatic-generation-medical-imaging-reports/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baoyu Jing, Pengtao Xie, Eric Xing*2018 · 484 citations*
107. [**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/)
108. **[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*
109. [**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/)
110. [**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/)
111. **[Distributional Semantics in Technicolor](https://md.research.elamur.ai/free/en/papers/bruni-2012-distributional-semantics-technicolor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Elia Bruni, Gemma Boleda, Marco Baroni, et al.*2012 · 462 citations*
112. [**Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents arXiv:2201.07207**Wenlong Huang, Pieter Abbeel, Deepak Pathak, et al.*2022 · 443 citations*](https://md.research.elamur.ai/free/en/papers/huang-2022-language-models-zero-shot-planners/)
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. **[Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling](https://md.research.elamur.ai/free/en/papers/hofstatter-2021-efficiently-teaching-effective-dense-retriever/) [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/)**Sebastian Hofstatter, Sheng-Chieh Lin, Jheng-Hong Yang, et al.*2021 · 425 citations*
115. **[WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents](https://md.research.elamur.ai/free/en/papers/yao-2022-webshop-towards-scalable-real-world/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shunyu Yao, Howard Chen, John Yang, et al.*2022 · 420 citations*
116. **[Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning](https://md.research.elamur.ai/free/en/papers/gordon-2020-compressing-bert-studying-effects-weight/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Mitchell Gordon, Kevin Duh, Nicholas Andrews*2020 · 407 citations*
117. **[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*
118. [**FiLM: Visual Reasoning with a General Conditioning Layer arXiv:1709.07871**Ethan Perez, Florian Strub, Harm de Vries, et al.*2017 · 400 citations*](https://md.research.elamur.ai/free/en/papers/perez-2017-film-visual-reasoning-general-conditioning/)
119. **[ViperGPT: Visual Inference via Python Execution for Reasoning](https://md.research.elamur.ai/free/en/papers/suris-2023-vipergpt-visual-inference-python-execution/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Didac Suris, Sachit Menon, Carl Vondrick*2023 · 383 citations*
120. **[VILA: On Pre-training for Visual Language Models](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-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/)**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 381 citations*
121. [**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/)
122. **[Analyzing the Behavior of Visual Question Answering Models](https://md.research.elamur.ai/free/en/papers/agrawal-2016-analyzing-behavior-visual-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aishwarya Agrawal, Dhruv Batra, Devi Parikh*2016 · 371 citations*
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. **[QuestEval: Summarization Asks for Fact-based Evaluation](https://md.research.elamur.ai/free/en/papers/scialom-2021-questeval-summarization-asks-fact-based/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al.*2021 · 359 citations*
125. **[Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout](https://md.research.elamur.ai/free/en/papers/tan-2019-learning-navigate-unseen-environments-back/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hao Tan, Licheng Yu, Mohit Bansal*2019 · 358 citations*
126. **[Generating Natural Questions About an Image](https://md.research.elamur.ai/free/en/papers/mostafazadeh-2016-generating-natural-questions-about-image/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, et al.*2016 · 343 citations*
127. [**An Actor-Critic Algorithm for Sequence Prediction arXiv:1607.07086**Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, et al.*2016 · 335 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2016-actor-critic-algorithm-sequence-prediction/)
128. **[Search-based Neural Structured Learning for Sequential Question Answering](https://md.research.elamur.ai/free/en/papers/iyyer-2017-search-based-neural-structured-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohit Iyyer, Wen-tau Yih, Ming-Wei Chang*2017 · 330 citations*
129. **[How Transferable are Neural Networks in NLP Applications?](https://md.research.elamur.ai/free/en/papers/mou-2016-how-transferable-are-neural-networks/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lili Mou, Zhao Meng, Rui Yan, et al.*2016 · 328 citations*
130. **[Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Pan Lu, Baolin Peng, Hao Cheng, et al.*2023 · 327 citations*
131. [**ALFWorld: Aligning Text and Embodied Environments for Interactive Learning arXiv:2010.03768**Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, et al.*2020 · 322 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2020-alfworld-aligning-text-embodied-environments/)
132. [**Multi-task Sequence to Sequence Learning arXiv:1511.06114**Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, et al.*2015 · 321 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-multi-task-sequence-sequence-learning/)
133. **[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*
134. **[Cross-Language Text Classification Using Structural Correspondence Learning](https://md.research.elamur.ai/free/en/papers/prettenhofer-2010-cross-language-text-classification-structural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peter Prettenhofer, Benno Stein*2010 · 315 citations*
135. **[A Survey of Domain Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2018-survey-domain-adaptation-neural-machine/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chenhui Chu, Rui Wang*2018 · 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. [**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/)
138. **[Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 295 citations*
139. **[Black Holes and White Rabbits: Metaphor Identification with Visual Features](https://md.research.elamur.ai/free/en/papers/shutova-2016-black-holes-white-rabbits-metaphor/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ekaterina Shutova, Douwe Kiela, Jean Maillard*2016 · 293 citations*
140. **[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*
141. [**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/)
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. **[Guided Open Vocabulary Image Captioning with Constrained Beam Search](https://md.research.elamur.ai/free/en/papers/anderson-2017-guided-open-vocabulary-image-captioning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peter Anderson, Basura Fernando, Mark Johnson, et al.*2017 · 286 citations*
144. [**Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models arXiv:1610.02424**Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, et al.*2016 · 282 citations*](https://md.research.elamur.ai/free/en/papers/vijayakumar-2016-diverse-beam-search-decoding-diverse/)
145. **[TRUE: Re-evaluating Factual Consistency Evaluation](https://md.research.elamur.ai/free/en/papers/honovich-2022-true-re-evaluating-factual-consistency/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Or Honovich, Roee Aharoni, Jonathan Herzig, et al.*2022 · 279 citations*
146. **[Surface Form Competition: Why the Highest Probability Answer Isn't Always Right](https://md.research.elamur.ai/free/en/papers/holtzman-2021-surface-form-competition-why-highest/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ari Holtzman, Peter West, Vered Shwartz, et al.*2021 · 277 citations*
147. **[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*
148. [**Towards Understanding and Mitigating Social Biases in Language Models arXiv:2106.13219**Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.*2021 · 271 citations*](https://md.research.elamur.ai/free/en/papers/liang-2021-towards-understanding-mitigating-social-biases/)
149. [**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/)
150. **[Handling Divergent Reference Texts when Evaluating Table-to-Text Generation](https://md.research.elamur.ai/free/en/papers/dhingra-2019-handling-divergent-reference-texts-when/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhuwan Dhingra, Manaal Faruqui, Ankur Parikh, et al.*2019 · 268 citations*
151. **[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*
152. **[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*
153. [**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/)
154. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
155. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
156. **[Attention-based Multimodal Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/huang-2016-attention-based-multimodal-neural-machine/) [Conference on Machine Translation: Shared Task Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-shared-task-papers/)**Po-Yao Huang, Frederick Liu, Sz-Rung Shiang, et al.*2016 · 236 citations*
157. [**Gradient Surgery for Multi-Task Learning arXiv:2001.06782**Tianhe Yu, Saurabh Kumar, Abhishek Gupta, et al.*2020 · 233 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-gradient-surgery-multi-task-learning/)
158. **[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*
159. [**A Diagram Is Worth A Dozen Images arXiv:1603.07396**Aniruddha Kembhavi, Mike Salvato, Eric Kolve, et al.*2016 · 231 citations*](https://md.research.elamur.ai/free/en/papers/kembhavi-2016-diagram-worth-dozen-images/)
160. [**A Survey of Hallucination in Large Foundation Models arXiv:2309.05922**Vipula Rawte, Amit Sheth, Amitava Das*2023 · 226 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-survey-hallucination-large-foundation-models/)
161. [**How Language Model Hallucinations Can Snowball arXiv:2305.13534**Muru Zhang, Ofir Press, William Merrill, et al.*2023 · 226 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-language-model-hallucinations-snowball/)
162. **[Break It Down: A Question Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 222 citations*
163. **[Unsupervised Question Decomposition for Question Answering](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 222 citations*
164. **[Structured Pruning Learns Compact and Accurate Models](https://md.research.elamur.ai/free/en/papers/xia-2022-structured-pruning-learns-compact-accurate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengzhou Xia, Zexuan Zhong, Danqi Chen*2022 · 221 citations*
165. **[Measuring Association Between Labels and Free-Text Rationales](https://md.research.elamur.ai/free/en/papers/wiegreffe-2021-measuring-association-between-labels-free/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sarah Wiegreffe, Ana Marasović, Noah A. Smith*2021 · 220 citations*
166. [**Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch arXiv:2311.03099**Le Yu, Bowen Yu, Haiyang Yu, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-language-models-super-mario-absorbing/)
167. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
168. **[Did the Model Understand the Question?](https://md.research.elamur.ai/free/en/papers/mudrakarta-2018-did-model-understand-question/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pramod Kaushik Mudrakarta, Ankur Taly, Mukund Sundararajan, et al.*2018 · 214 citations*
169. **[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*
170. [**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/)
171. **[Logical Natural Language Generation from Open-Domain Tables](https://md.research.elamur.ai/free/en/papers/chen-2020-logical-natural-language-generation-open/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhu Chen, Jianshu Chen, Yu Su, et al.*2020 · 210 citations*
172. **[Active Example Selection for In-Context Learning](https://md.research.elamur.ai/free/en/papers/zhang-2022-active-example-selection-context-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yiming Zhang, Shi Feng, Chenhao Tan*2022 · 209 citations*
173. **[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*
174. **[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*
175. **[Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview](https://md.research.elamur.ai/free/en/papers/shah-2019-predictive-biases-natural-language-processing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deven Shah, H. Andrew Schwartz, Dirk Hovy*2019 · 207 citations*
176. [**MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning arXiv:2310.09478**Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.*2023 · 199 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-minigpt-v2-large-language-model/)
177. **[Towards Faithful Model Explanation in NLP: A Survey](https://md.research.elamur.ai/free/en/papers/lyu-2024-faithful-model-explanation-nlp-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Qing Lyu, Marianna Apidianaki, Chris Callison-Burch*2024 · 197 citations*
178. **[The Right Tool for the Job: Matching Model and Instance Complexities](https://md.research.elamur.ai/free/en/papers/schwartz-2020-right-tool-job-matching-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, et al.*2020 · 196 citations*
179. **[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*
180. **[Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning](https://md.research.elamur.ai/free/en/papers/guo-2019-densely-connected-graph-convolutional-networks/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Yan Zhang, Zhiyang Teng, et al.*2019 · 193 citations*
181. [**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/)
182. **[AudioCaps: Generating Captions for Audios in The Wild](https://md.research.elamur.ai/free/en/papers/kim-2019-audiocaps-generating-captions-audios-wild/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, et al.*2019 · 187 citations*
183. **[GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2021-geoqa-geometric-question-answering-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaqi Chen, Jianheng Tang, Jinghui Qin, et al.*2021 · 184 citations*
184. **[NILE : Natural Language Inference with Faithful Natural Language Explanations](https://md.research.elamur.ai/free/en/papers/kumar-2020-nile-natural-language-inference-faithful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sawan Kumar, Partha Talukdar*2020 · 184 citations*
185. **[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*
186. **[Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control](https://md.research.elamur.ai/free/en/papers/yu-2019-rethinking-cooperative-rationalization-introspective-extraction/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mo Yu, Shiyu Chang, Yang Zhang, et al.*2019 · 179 citations*
187. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
188. [**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/)
189. **[Lifting the Curse of Multilinguality by Pre-training Modular Transformers](https://md.research.elamur.ai/free/en/papers/pfeiffer-2022-lifting-curse-multilinguality-pre-training/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jonas Pfeiffer, Naman Goyal, Xi Victoria Lin, et al.*2022 · 174 citations*
190. **[Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2019-addressing-semantic-drift-question-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shiyue Zhang, Mohit Bansal*2019 · 174 citations*
191. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision arXiv:2312.09390**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
192. [**DeepProbLog: Neural Probabilistic Logic Programming arXiv:1805.10872**Robin Manhaeve, Sebastijan Dumančić, Angelika Kimmig, et al.*2018 · 172 citations*](https://md.research.elamur.ai/free/en/papers/manhaeve-2018-deepproblog-neural-probabilistic-logic/)
193. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
194. [**Binding Language Models in Symbolic Languages arXiv:2210.02875**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 170 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/)
195. **[Semantic Noise Matters for Neural Natural Language Generation](https://md.research.elamur.ai/free/en/papers/dusek-2019-semantic-noise-matters-neural-natural/) [International Natural Language Generation Conference (INLG)](https://md.research.elamur.ai/free/en/venues/inlg/)**Ondřej Dušek, David M. Howcroft, Verena Rieser*2019 · 164 citations*
196. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 161 citations*
197. [**Reasoning with Language Model Prompting: A Survey arXiv:2212.09597**Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.*2022 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2022-reasoning-language-model-prompting-survey/)
198. [**SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training arXiv:2501.17161**Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.*2025 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chu-2025-sft-memorizes-rl-generalizes-comparative/)
199. **[On Hallucination and Predictive Uncertainty in Conditional Language Generation](https://md.research.elamur.ai/free/en/papers/xiao-2021-hallucination-predictive-uncertainty-conditional-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yijun Xiao, William Yang Wang*2021 · 157 citations*
200. **[Automatic Stance Detection Using End-to-End Memory Networks](https://md.research.elamur.ai/free/en/papers/mohtarami-2018-automatic-stance-detection-end-end/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mitra Mohtarami, Ramy Baly, James Glass, et al.*2018 · 157 citations*

[← prev](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/3/) [4](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/4/) [5](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/5/) [next →](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/cited-by/page/3/)

- [← back to](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/) — Trevor Jackson Darrell