---
title: "Who cites Justin M. Johnson — page 2 — 1,478 citing papers"
description: "1,478 papers of the Elamur Research library cite the works of Justin M. Among them: Break It Down: A Question Understanding Benchmark…"
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# Who cites Justin M. Johnson

1,766 citations of their works from 1,478 papers of our library (of the 149,439 whose bibliographies we read) · 208 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Justin M. Johnson](https://md.research.elamur.ai/free/en/authors/justin-m-johnson/)

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101. **[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*
102. **[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*
103. **[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*
104. [**Compositional Attention Networks for Machine Reasoning arXiv:1803.03067**Drew A. Hudson, Christopher D. Manning*2018 · 213 citations*](https://md.research.elamur.ai/free/en/papers/hudson-2018-compositional-attention-networks-machine-reasoning/)
105. **[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*
106. [**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/)
107. **[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*
108. **[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*
109. **[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*
110. **[The emergence of number and syntax units in LSTM language models](https://md.research.elamur.ai/free/en/papers/lakretz-2019-emergence-number-syntax-units-lstm/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yair Lakretz, German Kruszewski, Theo Desbordes, et al.*2019 · 194 citations*
111. **[Representation of Linguistic Form and Function in Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/kadar-2017-representation-linguistic-form-function-recurrent/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ákos Kádár, Grzegorz Chrupała, Afra Alishahi*2017 · 192 citations*
112. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
113. [**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/)
114. **[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*
115. **[Learning Language Representations for Typology Prediction](https://md.research.elamur.ai/free/en/papers/malaviya-2017-learning-language-representations-typology-prediction/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chaitanya Malaviya, Graham Neubig, Patrick Littell*2017 · 187 citations*
116. **[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*
117. **[AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models](https://md.research.elamur.ai/free/en/papers/wallace-2019-allennlp-interpret-framework-explaining-predictions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Wallace, Jens Tuyls, Junlin Wang, et al.*2019 · 182 citations*
118. **[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*
119. [**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/)
120. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
121. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations*
122. [**Compositionality decomposed: how do neural networks generalise? arXiv:1908.08351**Dieuwke Hupkes, Verna Dankers, Mathijs Mul, et al.*2019 · 162 citations*](https://md.research.elamur.ai/free/en/papers/hupkes-2019-compositionality-decomposed-neural-networks-generalise/)
123. [**ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph arXiv:2006.16934**Fei Yu, Jiji Tang, Weichong Yin, et al.*2020 · 152 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-ernie-vil-knowledge-enhanced/)
124. **[Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs](https://md.research.elamur.ai/free/en/papers/bugliarello-2021-multimodal-pretraining-unmasked-meta-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, et al.*2021 · 141 citations*
125. **[LLaVA-CoT: Let Vision Language Models Reason Step-by-Step](https://md.research.elamur.ai/free/en/papers/xu-2024-llava-cot-let-vision-language/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Guowei Xu, Peng Jin, Ziang Wu, et al.*2024 · 138 citations*
126. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches arXiv:1904.01172**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 135 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
127. [**Scaling Vision with Sparse Mixture of Experts arXiv:2106.05974**Carlos Riquelme, Joan Puigcerver, Basil Mustafa, et al.*2021 · 128 citations*](https://md.research.elamur.ai/free/en/papers/riquelme-2021-scaling-vision-sparse-mixture-experts/)
128. **[FOIL it! Find One mismatch between Image and Language caption](https://md.research.elamur.ai/free/en/papers/shekhar-2017-foil-it-find-one-mismatch/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ravi Shekhar, Sandro Pezzelle, Yauhen Klimovich, et al.*2017 · 127 citations*
129. [**Identifying and Controlling Important Neurons in Neural Machine Translation arXiv:1811.01157**Anthony Bau, Yonatan Belinkov, Hassan Sajjad, et al.*2018 · 121 citations*](https://md.research.elamur.ai/free/en/papers/bau-2018-identifying-controlling-important-neurons-neural/)
130. [**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/)
131. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
132. **[Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/shao-2024-visual-cot-advancing-multi-modal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hao Shao, Shengju Qian, Han Xiao, et al.*2024 · 117 citations*
133. **[Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation](https://md.research.elamur.ai/free/en/papers/mou-2016-sequence-backward-forward-sequences-content/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Lili Mou, Yiping Song, Rui Yan, et al.*2016 · 117 citations*
134. **[UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression](https://md.research.elamur.ai/free/en/papers/chen-2022-unigeo-unifying-geometry-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaqi Chen, Tong Li, Jinghui Qin, et al.*2022 · 111 citations*
135. [**Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework**Aaron Steven White, Pushpendre Rastogi, Kevin Duh, et al.*2017 · 110 citations*](https://md.research.elamur.ai/free/en/papers/white-2017-inference-is-everything-recasting-semantic/)
136. **[Look at the First Sentence: Position Bias in Question Answering](https://md.research.elamur.ai/free/en/papers/ko-2020-look-first-sentence-position-bias/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, et al.*2020 · 104 citations*
137. [**IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning arXiv:2110.13214**Pan Lu, Liang Qiu, Jiaqi Chen, et al.*2021 · 103 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-iconqa-new-benchmark-abstract-diagram/)
138. [**LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding arXiv:2306.17107**Yanzhe Zhang, Ruiyi Zhang, Jiuxiang Gu, et al.*2023 · 98 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llavar-enhanced-visual-instruction-tuning/)
139. **[Crossmodal-3600: A Massively Multilingual Multimodal Evaluation Dataset](https://md.research.elamur.ai/free/en/papers/thapliyal-2022-crossmodal-3600-massively-multilingual-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ashish V. Thapliyal, Jordi Pont Tuset, Xi Chen, et al.*2022 · 95 citations*
140. [**SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning**Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.*2021 · 95 citations*](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)
141. **[CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication](https://md.research.elamur.ai/free/en/papers/kim-2019-codraw-collaborative-drawing-as-testbed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin-Hwa Kim, Nikita Kitaev, Xinlei Chen, et al.*2019 · 94 citations*
142. [**Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models arXiv:2503.06749**Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/huang-2025-vision-r1-incentivizing-reasoning-capability/)
143. **[Interpreting Neural Networks to Improve Politeness Comprehension](https://md.research.elamur.ai/free/en/papers/aubakirova-2016-interpreting-neural-networks-improve-politeness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Malika Aubakirova, Mohit Bansal*2016 · 87 citations*
144. **[Finding Skill Neurons in Pre-trained Transformer-based Language Models](https://md.research.elamur.ai/free/en/papers/wang-2022-finding-skill-neurons-pre-trained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaozhi Wang, Kaiyue Wen, Zhengyan Zhang, et al.*2022 · 85 citations*
145. **[Neuron-level Interpretation of Deep NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/sajjad-2022-neuron-level-interpretation-deep-nlp/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Hassan Sajjad, Nadir Durrani, Fahim Dalvi*2022 · 85 citations*
146. [**What Do Recurrent Neural Network Grammars Learn About Syntax? arXiv:1611.05774**Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, et al.*2016 · 83 citations*](https://md.research.elamur.ai/free/en/papers/kuncoro-2016-recurrent-neural-network-grammars-learn/)
147. [**Wider and Deeper LLM Networks are Fairer LLM Evaluators arXiv:2308.01862**Xinghua Zhang, Bowen Yu, Haiyang Yu, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-wider-deeper-llm-networks-fairer/)
148. [**Systematic Generalization: What Is Required and Can It Be Learned? arXiv:1811.12889**Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, et al.*2018 · 73 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2018-systematic-generalization-required-learned/)
149. **[RNNs can generate bounded hierarchical languages with optimal memory](https://md.research.elamur.ai/free/en/papers/hewitt-2020-rnns-can-generate-bounded-hierarchical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John Hewitt, Michael Hahn, Surya Ganguli, et al.*2020 · 65 citations*
150. [**ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models arXiv:2402.11684**Guiming Hardy Chen, Shunian Chen, Ruifei Zhang, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-allava-harnessing-gpt4v-synthesized-data/)
151. [**MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning arXiv:2309.07915**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-mmicl-empowering-vision-language-model/)
152. **[The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue](https://md.research.elamur.ai/free/en/papers/haber-2019-photobook-dataset-building-common-ground/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Janosch Haber, Tim Baumgärtner, Ece Takmaz, et al.*2019 · 53 citations*
153. [**CogVLM2: Visual Language Models for Image and Video Understanding arXiv:2408.16500**Wenyi Hong, Weihan Wang, Ming Ding, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/hong-2024-cogvlm2-visual-language-models/)
154. [**Parameter-Efficient Fine-Tuning Design Spaces arXiv:2301.01821**Jiaao Chen, Aston Zhang, Xingjian Shi, et al.*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-parameter-efficient-fine-tuning-design/)
155. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
156. [**Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages arXiv:2308.12038**Jinyi Hu, Yuan Yao, Chongyi Wang, et al.*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-large-multilingual-models-pivot-zero/)
157. **[MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale](https://md.research.elamur.ai/free/en/papers/guo-2025-mammoth-vl-eliciting-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.*2025 · 40 citations*
158. **[Natural Language Inference from Multiple Premises](https://md.research.elamur.ai/free/en/papers/lai-2017-natural-language-inference-multiple-premises/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Alice Lai, Yonatan Bisk, Julia Hockenmaier*2017 · 39 citations*
159. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
160. **[Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al.*2023 · 38 citations*
161. [**SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models arXiv:2504.11468**Hardy Chen, Haoqin Tu, Fali Wang, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-sft-rl-early-investigation-training/)
162. **[Probing Contextual Language Models for Common Ground with Visual Representations](https://md.research.elamur.ai/free/en/papers/ilharco-2021-probing-contextual-language-models-common/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Gabriel Ilharco, Rowan Zellers, Ali Farhadi, et al.*2021 · 33 citations*
163. [**Know What You Don't Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories**Sina Zarrieß, David Schlangen*2019 · 24 citations*](https://md.research.elamur.ai/free/en/papers/zarriess-2019-know-what-you-don-t/)
164. [**COLLIE: Systematic Construction of Constrained Text Generation Tasks arXiv:2307.08689**Shunyu Yao, Howard Chen, Austin W. Hanjie, et al.*2023 · 23 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-collie-systematic-construction-constrained-text/)
165. **[Whodunnit? Crime Drama as a Case for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/frermann-2018-whodunnit-crime-drama-as-case/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Lea Frermann, Shay B. Cohen, Mirella Lapata*2018 · 22 citations*
166. [**ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning arXiv:2501.06590**Xiangru Tang, Tianyu Hu, Muyang Ye, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-chemagent-self-updating-library-large/)
167. **[Classifying ASR Transcriptions According to Arabic Dialect](https://md.research.elamur.ai/free/en/papers/hanani-2016-classifying-asr-transcriptions-according-arabic/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Abualsoud Hanani, Aziz Qaroush, Stephen Taylor*2016 · 15 citations*
168. **[Enhancing Automated Interpretability with Output-Centric Feature Descriptions](https://md.research.elamur.ai/free/en/papers/arieh-2025-enhancing-automated-interpretability-output-centric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yoav Gur-Arieh, Roy Mayan, Chen Agassy, et al.*2025 · 13 citations*
169. **[What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/du-2025-what-makes-good-visual-instructions/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yifan Du, Hangyu Guo, Kun Zhou, et al.*2025 · 13 citations*
170. **[DevBench: A multimodal developmental benchmark for language learning](https://md.research.elamur.ai/free/en/papers/tan-2024-devbench-multimodal-developmental-benchmark-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alvin Wei Ming Tan, Sunny Yu, Bria Long, et al.*2024 · 13 citations*
171. **[Maintaining Common Ground in Dynamic Environments](https://md.research.elamur.ai/free/en/papers/udagawa-2021-maintaining-common-ground-dynamic-environments/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Takuma Udagawa, Akiko Aizawa*2021 · 13 citations*
172. **[Can Multimodal Large Language Models Understand Spatial Relations?](https://md.research.elamur.ai/free/en/papers/liu-2025-can-multimodal-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingping Liu, Ziyan Liu, Zhedong Cen, et al.*2025 · 11 citations*
173. **[Scaffolding Coordinates to Promote Vision-Language Coordination in Large Multi-Modal Models](https://md.research.elamur.ai/free/en/papers/lei-2025-scaffolding-coordinates-promote-vision-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Xuanyu Lei, Zonghan Yang, Xinrui Chen, et al.*2025 · 11 citations*
174. **[Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](https://md.research.elamur.ai/free/en/papers/geigle-2025-centurio-drivers-multilingual-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.*2025 · 9 citations*
175. **[ViLBench: A Suite for Vision-Language Process Reward Modeling](https://md.research.elamur.ai/free/en/papers/tu-2025-vilbench-suite-vision-language-process/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoqin Tu, Weitao Feng, Hardy Chen, et al.*2025 · 9 citations*
176. **[VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search](https://md.research.elamur.ai/free/en/papers/jia-2025-visualwebinstruct-scaling-up-multimodal-instruction/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yiming Jia, Jiachen Li, Xiang Yue, et al.*2025 · 9 citations*
177. **[PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers](https://md.research.elamur.ai/free/en/papers/saxon-2023-peco-examining-single-sentence-label/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Michael Saxon, Xinyi Wang, Wenda Xu, et al.*2023 · 9 citations*
178. [**Survey of Abstract Meaning Representation: Then, Now, Future**Behrooz Mansouri*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/mansouri-2025-survey-abstract-meaning-representation-then/)
179. **[Insight Over Sight: Exploring the Vision-Knowledge Conflicts in Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-insight-over-sight-exploring-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Liu, Wenxuan Wang, Youliang Yuan, et al.*2025 · 6 citations*
180. **[Acquiring Linguistic Knowledge from Multimodal Input](https://md.research.elamur.ai/free/en/papers/amariucai-2023-acquiring-linguistic-knowledge-multimodal-input/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Theodor Amariucai, Alexander Scott Warstadt*2023 · 6 citations*
181. **[Comparing Knowledge-Intensive and Data-Intensive Models for English Resource Semantic Parsing](https://md.research.elamur.ai/free/en/papers/cao-2021-comparing-knowledge-intensive-data-intensive/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Junjie Cao, Zi Lin, Weiwei Sun, et al.*2021 · 6 citations*
182. **[OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-offside-benchmarking-unlearning-misinformation-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zheng, Zirui Pang, Ling Li, et al.*2026 · 4 citations*
183. [**Multimodal Arabic Captioning with Interpretable Visual Concept Integration arXiv:2510.03295**Passant Elchafei, Amany Fashwan*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/elchafei-2025-multimodal-arabic-captioning-interpretable-visual/)
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186. **[SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing](https://md.research.elamur.ai/free/en/papers/zhang-2026-sciflow-bench-evaluating-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tong Zhang, Honglin Lin, Zhou Liu, et al.*2026 · 1 citation*
187. **[Constructions All the Way Up: From Sensory Experiences to Construction Grammars](https://md.research.elamur.ai/free/en/papers/ekila-2025-constructions-all-way-up-sensory/) [International Workshop on Construction Grammars and NLP](https://md.research.elamur.ai/free/en/venues/cxgsnlp/)**Jérôme Botoko Ekila, Lara Verheyen, Katrien Beuls, et al.*2025 · 1 citation*
188. [**Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning arXiv:2205.09172**Fei Fang, Kunal Sinha, Noah D. Goodman, et al.*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/fang-2022-color-overmodification-emerges-data-driven/)
189. **[ANCHOR: LLM-driven Subject Conditioning for Text-to-Image Synthesis](https://md.research.elamur.ai/free/en/papers/ramakrishnan-2026-anchor-llm-driven-subject-conditioning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Aashish Anantha Ramakrishnan, Sharon X Huang, Dongwon Lee*2026*
190. **[Ask Me Again Differently: GRAS for Measuring Bias in Vision Language Models on Gender, Race, Age, and Skin Tone](https://md.research.elamur.ai/free/en/papers/malik-2026-ask-me-again-differently-gras/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shaivi Malik, Hasnat Md Abdullah, Sriparna Saha, et al.*2026*
191. **[Beyond Ranking: Fine-Grained Diagnostics and Self-Improvement for MLLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-beyond-ranking-fine-grained-diagnostics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingze Xu, Zijing Zhao, Qiming Peng, et al.*2026*
192. **[Common Objects Out of Context (COOCo): Investigating Multimodal Context and Semantic Scene Violations in Referential Communication](https://md.research.elamur.ai/free/en/papers/merlo-2026-common-objects-out-context-cooco/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Filippo Merlo, Ece Takmaz, Wenkai Chen, et al.*2026*
193. **[EVGeoQA: Benchmarking LLMs on Dynamic, Multi-Objective Geo-Spatial Exploration](https://md.research.elamur.ai/free/en/papers/wu-2026-evgeoqa-benchmarking-llms-dynamic-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianfei Wu, Zhichun Wang, Zhensheng Wang, et al.*2026*
194. **[Frame2KG: A Benchmark and Evaluation Toolkit for Interpretable Frame-to-Graph Generation](https://md.research.elamur.ai/free/en/papers/watson-2026-frame2kg-benchmark-evaluation-toolkit-interpretable/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Lewis N. Watson, Carl Strathearn, Kenny Mitchell, et al.*2026*
195. **[From Words to Pixels: A Comprehensive Survey on Large Language Models in Visual Segmentation](https://md.research.elamur.ai/free/en/papers/wang-2026-words-pixels-comprehensive-survey-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yizhou Wang, Mang Tik Chiu, Lingzhi Zhang, et al.*2026*
196. **[GeoQuery-LSFB: A French Belgian Sign Language Corpus with Procedural Semantic Annotations](https://md.research.elamur.ai/free/en/papers/vos-2026-geoquery-lsfb-french-belgian-sign/) [LREC Workshop on the Representation and Processing of Sign Languages: Language in Motion](https://md.research.elamur.ai/free/en/venues/signlang/)**Liesbet De Vos, Laurence Meurant, Paul Van Eecke, et al.*2026*
197. **[MEUR: A Benchmark for Evaluating Vision-Language Models on Multimodal Event Understanding and Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-meur-benchmark-evaluating-vision-language/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zimu Wang, Yuqi Wang, Tong Chen, et al.*2026*
198. **[Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/sinha-2026-mind-s-eye-benchmark-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rohit Sinha, Aditya Sanjiv Kanade, Sai Srinivas Kancheti, et al.*2026*
199. **[Mitigating Hallucinations in VLMs: Enhancing Visual Attention via Head-Wise Perturbation](https://md.research.elamur.ai/free/en/papers/wang-2026-mitigating-hallucinations-vlms-enhancing-visual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenghua Wang, Yixin Wu, Feiran Zhang, et al.*2026*
200. **[M³-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering](https://md.research.elamur.ai/free/en/papers/ma-2026-m-3-vqa-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatong Ma, Longteng Guo, Yuchen Liu, et al.*2026*

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