---
title: "Who cites Trevor Jackson — page 3 — 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 3 of 5 · 201–300…"
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---
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# 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 3 of 5 · 201–300 · [← Trevor Jackson Darrell](https://md.research.elamur.ai/free/en/authors/trevor-jackson-darrell/)

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201. **[LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding](https://md.research.elamur.ai/free/en/papers/elhoushi-2024-layerskip-enabling-early-exit-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, et al.*2024 · 156 citations*
202. **[Explaining NLP Models via Minimal Contrastive Editing (MiCE)](https://md.research.elamur.ai/free/en/papers/ross-2021-explaining-nlp-models-minimal-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alexis Ross, Ana Marasović, Matthew Peters*2021 · 155 citations*
203. **[Generating Sentences from Disentangled Syntactic and Semantic Spaces](https://md.research.elamur.ai/free/en/papers/bao-2019-generating-sentences-disentangled-syntactic-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Bao, Hao Zhou, Shujian Huang, et al.*2019 · 154 citations*
204. **[F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching](https://md.research.elamur.ai/free/en/papers/chen-2025-f5-tts-fairytaler-that-fakes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yushen Chen, Zhikang Niu, Ziyang Ma, et al.*2025 · 152 citations*
205. **[Simple and Effective Masked Diffusion Language Models](https://md.research.elamur.ai/free/en/papers/sahoo-2024-simple-effective-masked-diffusion-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, et al.*2024 · 152 citations*
206. **[Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding](https://md.research.elamur.ai/free/en/papers/dziri-2021-neural-path-hunter-reducing-hallucination/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nouha Dziri, Andrea Madotto, Osmar Zaïane, et al.*2021 · 152 citations*
207. **[Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks](https://md.research.elamur.ai/free/en/papers/dou-2019-investigating-meta-learning-algorithms-low/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zi-Yi Dou, Keyi Yu, Antonios Anastasopoulos*2019 · 150 citations*
208. **[Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2024-draft-verify-lossless-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jun Zhang, Jue Wang, Huan Li, et al.*2024 · 148 citations*
209. **[HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment](https://md.research.elamur.ai/free/en/papers/vulic-2017-hyperlex-large-scale-evaluation-graded/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ivan Vulić, Daniela Gerz, Douwe Kiela, et al.*2017 · 148 citations*
210. [**mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration arXiv:2311.04257**Qinghao Ye, Haiyang Xu, Jiabo Ye, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl2-revolutionizing-multi-modal/)
211. [**InternVideo: General Video Foundation Models via Generative and Discriminative Learning arXiv:2212.03191**Yi Wang, Kunchang Li, Yizhuo Li, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-internvideo-general-video-foundation/)
212. **[A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.*2022 · 142 citations*
213. [**DeepInception: Hypnotize Large Language Model to Be Jailbreaker arXiv:2311.03191**Xuan Li, Zhanke Zhou, Jianing Zhu, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-deepinception-hypnotize-large-language-model/)
214. **[Investigating Data Contamination in Modern Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*
215. **[Grounded Adaptation for Zero-shot Executable Semantic Parsing](https://md.research.elamur.ai/free/en/papers/zhong-2020-grounded-adaptation-zero-shot-executable/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Victor Zhong, Mike Lewis, Sida I. Wang, et al.*2020 · 136 citations*
216. **[ReFT: Reasoning with Reinforced Fine-Tuning](https://md.research.elamur.ai/free/en/papers/trung-2024-reft-reasoning-reinforced-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luong Trung, Xinbo Zhang, Zhanming Jie, et al.*2024 · 134 citations*
217. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
218. **[Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 129 citations*
219. [**Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning arXiv:2303.15647**Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-scaling-down-scale-up-guide/)
220. [**Fine-tuning Language Models for Factuality arXiv:2311.08401**Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-fine-tuning-language-models-factuality/)
221. **[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*
222. **[Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language?](https://md.research.elamur.ai/free/en/papers/hase-2020-leakage-adjusted-simulatability-can-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peter Hase, Shiyue Zhang, Harry Xie, et al.*2020 · 126 citations*
223. [**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/)
224. **[Aligning Faithful Interpretations with their Social Attribution](https://md.research.elamur.ai/free/en/papers/jacovi-2021-aligning-faithful-interpretations-their-social/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Alon Jacovi, Yoav Goldberg*2021 · 123 citations*
225. **[ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/asai-2022-attempt-parameter-efficient-multi-task/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akari Asai, Mohammadreza Salehi, Matthew Peters, et al.*2022 · 122 citations*
226. [**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/)
227. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
228. [**DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search arXiv:2408.08152**Huajian Xin, Z. Z. Ren, Junxiao Song, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-v1-5-harnessing/)
229. [**LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition arXiv:2307.13269**Chengsong Huang, Qian Liu, Bill Yuchen Lin, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-lorahub-efficient-cross-task-generalization/)
230. **[Learning Language Specific Sub-network for Multilingual Machine Translation](https://md.research.elamur.ai/free/en/papers/lin-2021-learning-language-specific-sub-network/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zehui Lin, Liwei Wu, Mingxuan Wang, et al.*2021 · 104 citations*
231. [**Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction**Zhanming Jie, Jierui Li, Wei Lu*2022 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jie-2022-learning-reason-deductively-math-word/)
232. [**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/)
233. [**TextGrad: Automatic "Differentiation" via Text arXiv:2406.07496**Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/yuksekgonul-2024-textgrad-automatic-differentiation-text/)
234. **[Cross-Domain Label-Adaptive Stance Detection](https://md.research.elamur.ai/free/en/papers/hardalov-2021-cross-domain-label-adaptive-stance/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2021 · 96 citations*
235. **[Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models](https://md.research.elamur.ai/free/en/papers/khot-2021-text-modular-networks-learning-decompose/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tushar Khot, Daniel Khashabi, Kyle Richardson, et al.*2021 · 95 citations*
236. **[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*
237. **[Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes](https://md.research.elamur.ai/free/en/papers/kim-2021-perspective-taking-pragmatics-generating-empathetic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyunwoo Kim, Byeongchang Kim, Gunhee Kim*2021 · 90 citations*
238. **[ADaPT: As-Needed Decomposition and Planning with Language Models](https://md.research.elamur.ai/free/en/papers/prasad-2024-adapt-as-needed-decomposition-planning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Archiki Prasad, Alexander Koller, Mareike Hartmann, et al.*2024 · 89 citations*
239. [**Rethinking Interpretability in the Era of Large Language Models arXiv:2402.01761**Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-rethinking-interpretability-era-large-language/)
240. **[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*
241. **[Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness](https://md.research.elamur.ai/free/en/papers/kim-2020-will-i-sound-like-me/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyunwoo Kim, Byeongchang Kim, Gunhee Kim*2020 · 83 citations*
242. **[Factuality of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2024-factuality-large-language-models-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxia Wang, Minghan Wang, Muhammad Arslan Manzoor, et al.*2024 · 77 citations*
243. [**Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models arXiv:2305.14705**Sheng Shen, Le Hou, Yanqi Zhou, et al.*2023 · 70 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-mixture-experts-meets-instruction-tuning/)
244. **[Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-alignment-factuality-mitigating-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoying Zhang, Baolin Peng, Ye Tian, et al.*2024 · 69 citations*
245. [**Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning arXiv:2309.05444**Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/zadouri-2023-pushing-mixture-experts-limit-extremely/)
246. **[VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation](https://md.research.elamur.ai/free/en/papers/ku-2024-viescore-explainable-metrics-conditional-image/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Max Ku, Dongfu Jiang, Cong Wei, et al.*2024 · 68 citations*
247. **[Dependency Tree-based Sentiment Classification using CRFs with Hidden Variables](https://md.research.elamur.ai/free/en/papers/nakagawa-2010-dependency-tree-based-sentiment-classification/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tetsuji Nakagawa, Kentaro Inui, Sadao Kurohashi*2010 · 66 citations*
248. [**Exploring the Benefits of Training Expert Language Models over Instruction Tuning arXiv:2302.03202**Joel Jang, Seungone Kim, Seonghyeon Ye, et al.*2023 · 63 citations*](https://md.research.elamur.ai/free/en/papers/jang-2023-exploring-benefits-training-expert-language/)
249. [**Large Language Model Routing with Benchmark Datasets arXiv:2309.15789**Tal Shnitzer, Anthony Ou, Mirian Silva, et al.*2023 · 63 citations*](https://md.research.elamur.ai/free/en/papers/shnitzer-2023-large-language-model-routing-benchmark/)
250. [**MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark arXiv:2402.04788**Dongping Chen, Ruoxi Chen, Shilin Zhang, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mllm-judge-assessing-multimodal-llm/)
251. **[Bias in Large Language Models: Origin, Evaluation, and Mitigation](https://md.research.elamur.ai/free/en/papers/guo-2024-bias-large-language-models-origin/) [Electronics](https://md.research.elamur.ai/free/en/venues/electronics/)**Yufei Guo, Muzhe Guo, Juntao Su, et al.*2024 · 58 citations*
252. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations*
253. **[M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/chen-2024-m-3-cot-novel-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiguang Chen, Libo Qin, Jin Zhang, et al.*2024 · 54 citations*
254. **[mDPO: Conditional Preference Optimization for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-mdpo-conditional-preference-optimization-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fei Wang, Wenxuan Zhou, James Y. Huang, et al.*2024 · 50 citations*
255. **[Unfamiliar Finetuning Examples Control How Language Models Hallucinate](https://md.research.elamur.ai/free/en/papers/kang-2025-unfamiliar-finetuning-examples-control-how/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Katie Kang, Eric Wallace, Claire Tomlin, et al.*2025 · 47 citations*
256. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
257. [**Part-of-Speech Tagging for Historical English**Yi Yang, Jacob Eisenstein*2016 · 45 citations*](https://md.research.elamur.ai/free/en/papers/yang-2016-part-speech-tagging-historical-english/)
258. [**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/)
259. **[Improve Vision Language Model Chain-of-thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-improve-vision-language-model-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.*2025 · 42 citations*
260. [**SALMON: Self-Alignment with Instructable Reward Models arXiv:2310.05910**Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-salmon-self-alignment-instructable-reward/)
261. **[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*
262. **[Sociodemographic Bias in Language Models: A Survey and Forward Path](https://md.research.elamur.ai/free/en/papers/gupta-2023-sociodemographic-bias-language-models-survey/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Vipul Gupta, Pranav Narayanan Venkit, Shomir Wilson, et al.*2023 · 40 citations*
263. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
264. **[Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data](https://md.research.elamur.ai/free/en/papers/akhtar-2023-exploring-numerical-reasoning-capabilities-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.*2023 · 38 citations*
265. **[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*
266. [**SlimPajama-DC: Understanding Data Combinations for LLM Training arXiv:2309.10818**Zhiqiang Shen, Tianhua Tao, Liqun Ma, et al.*2023 · 38 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-slimpajama-dc-understanding-data-combinations/)
267. **[Continual Adaptation for Efficient Machine Communication](https://md.research.elamur.ai/free/en/papers/hawkins-2020-continual-adaptation-efficient-machine-communication/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Robert Hawkins, Minae Kwon, Dorsa Sadigh, et al.*2020 · 38 citations*
268. **[Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory](https://md.research.elamur.ai/free/en/papers/suzgun-2026-dynamic-cheatsheet-test-time-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi, et al.*2026 · 37 citations*
269. [**MiMo-VL Technical Report arXiv:2506.03569**Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-vl-technical-report/)
270. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
271. **[Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward](https://md.research.elamur.ai/free/en/papers/zhang-2025-direct-preference-optimization-video-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ruohong Zhang, Liangke Gui, Zhiqing Sun, et al.*2025 · 32 citations*
272. [**Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation arXiv:2305.18846**Minki Kang, Jin Myung Kwak, Jinheon Baek, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/kang-2023-knowledge-graph-augmented-language-models/)
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274. **[G-Safeguard: A Topology-Guided Security Lens and Treatment on LLM-based Multi-agent Systems](https://md.research.elamur.ai/free/en/papers/wang-2025-g-safeguard-topology-guided-security/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shilong Wang, Guibin Zhang, Miao Yu, et al.*2025 · 30 citations*
275. **[PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides](https://md.research.elamur.ai/free/en/papers/zheng-2025-pptagent-generating-evaluating-presentations-beyond/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Zheng, Xinyan Guan, Hao Kong, et al.*2025 · 30 citations*
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278. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
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282. **[Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/chrysostomou-2024-investigating-hallucinations-pruned-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**George Chrysostomou, Zhixue Zhao, Miles Williams, et al.*2024 · 27 citations*
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284. [**Gapping Constructions in Universal Dependencies v2**Sebastian Schuster, Matthew Lamm, Christopher D. Manning*2017 · 25 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2017-gapping-constructions-universal-dependencies-v2/)
285. [**MiMo-Audio: Audio Language Models are Few-Shot Learners arXiv:2512.23808**Xiaomi LLM-Core Team, Dong Zhang, Gang Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/)
286. [**MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe arXiv:2509.18154**Tianyu Yu, Zefan Wang, Chongyi Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-minicpm-v-4-5/)
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288. [**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/)
289. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/)
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292. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
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294. [**ModuleFormer: Modularity Emerges from Mixture-of-Experts arXiv:2306.04640**Yikang Shen, Zheyu Zhang, Tianyou Cao, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-moduleformer-modularity-emerges-mixture-experts/)
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296. [**The Vector Grounding Problem arXiv:2304.01481**Dimitri Coelho Mollo, Raphael Milliere*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/mollo-2023-vector-grounding-problem/)
297. **[Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-beyond-chain-thought-survey-chain/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yu Xia, Rui Wang, Xu Liu, et al.*2025 · 19 citations*
298. **[Propaganda to Hate: A Multimodal Analysis of Arabic Memes with Multi-Agent LLMs](https://md.research.elamur.ai/free/en/papers/alam-2024-propaganda-hate-multimodal-analysis-arabic/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Firoj Alam, Md. Rafiul Biswas, Uzair Shah, et al.*2024 · 18 citations*
299. **[Violet: A Vision-Language Model for Arabic Image Captioning with Gemini Decoder](https://md.research.elamur.ai/free/en/papers/mohamed-2023-violet-vision-language-model-arabic/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Abdelrahman Mohamed, Fakhraddin Alwajih, El Moatez Billah Nagoudi, et al.*2023 · 18 citations*
300. **[TADA : Task Agnostic Dialect Adapters for English](https://md.research.elamur.ai/free/en/papers/held-2023-tada-task-agnostic-dialect-adapters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**William Held, Caleb Ziems, Diyi Yang*2023 · 17 citations*

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