---
title: "Who cites Xinlong Wang — 440 papers of our library"
description: "440 papers of the Elamur Research library cite the works of Xinlong Wang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/xinlong-wang/cited-by/"
---
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# Who cites Xinlong Wang

459 citations of their works from 440 papers of our library (of the 149,439 whose bibliographies we read) · 89 with a page here, the most cited first · [← Xinlong Wang](https://md.research.elamur.ai/free/en/authors/xinlong-wang/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. **[Improved Baselines with Visual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/liu-2023-improved-baselines-visual-instruction-tuning/) [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/)**Haotian Liu, Chunyuan Li, Yuheng Li, et al.*2023 · 2,614 citations*
3. [**BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models arXiv:2301.12597**Junnan Li, Dongxu Li, Silvio Savarese, et al.*2023 · 2,219 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-blip-2-bootstrapping-language-image/)
4. [**DINOv2: Learning Robust Visual Features without Supervision arXiv:2304.07193**Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.*2023 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/oquab-2023-dinov2-learning-robust-visual-features/)
5. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
6. [**MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models arXiv:2304.10592**Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.*2023 · 1,141 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-minigpt-4-enhancing-vision-language/)
7. [**InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning arXiv:2305.06500**Wenliang Dai, Junnan Li, Dongxu Li, et al.*2023 · 1,100 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-instructblip-towards-general-purpose-vision/)
8. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 978 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/)
9. **[Reproducible scaling laws for contrastive language-image learning](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-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/)**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 769 citations*
10. [**Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model arXiv:2401.09417**Lianghui Zhu, Bencheng Liao, Qian Zhang, et al.*2024 · 500 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-vision-mamba-efficient-visual-representation/)
11. **[MVBench: A Comprehensive Multi-modal Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 463 citations*
12. **[ShareGPT4V: Improving Large Multi-Modal Models with Better Captions](https://md.research.elamur.ai/free/en/papers/chen-2023-sharegpt4v-improving-large-multi-modal/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2023 · 454 citations*
13. [**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/)
14. **[CogVLM: Visual Expert for Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-cogvlm-visual-expert-pretrained/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Weihan Wang, Qingsong Lv, Wenmeng Yu, et al.*2023 · 383 citations*
15. **[CogAgent: A Visual Language Model for GUI Agents](https://md.research.elamur.ai/free/en/papers/hong-2023-cogagent-visual-language-model/) [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/)**Wenyi Hong, Weihan Wang, Qingsong Lv, et al.*2023 · 367 citations*
16. **[VideoChat: Chat-Centric Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2023-videochat-chat-centric-video-understanding/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**KunChang Li, Yinan He, Yi Wang, et al.*2023 · 365 citations*
17. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
18. **[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*
19. [**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/)
20. **[LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-llama-vid-image-worth-2/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yanwei Li, Chengyao Wang, Jiaya Jia*2023 · 262 citations*
21. **[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*
22. **[Visual Adversarial Examples Jailbreak Aligned Large Language Models](https://md.research.elamur.ai/free/en/papers/qi-2023-visual-adversarial-examples-jailbreak-aligned/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.*2023 · 240 citations*
23. **[OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation](https://md.research.elamur.ai/free/en/papers/huang-2023-opera-alleviating-hallucination-multi-modal/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Qidong Huang, Xiaoyi Dong, Pan Zhang, et al.*2023 · 238 citations*
24. [**Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding arXiv:2306.02858**Hang Zhang, Xin Li, Lidong Bing*2023 · 238 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-video-llama-instruction-tuned-audio/)
25. [**Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models arXiv:2405.01535**Seungone Kim, Juyoung Suk, Shayne Longpre, et al.*2024 · 234 citations*](https://md.research.elamur.ai/free/en/papers/kim-2024-prometheus-2-open-source-language/)
26. **[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*
27. **[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*
28. **[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*
29. [**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/)
30. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
31. **[FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts](https://md.research.elamur.ai/free/en/papers/gong-2023-figstep-jailbreaking-large-vision-language/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yichen Gong, Delong Ran, Jinyuan Liu, et al.*2023 · 163 citations*
32. **[Are aligned neural networks adversarially aligned?](https://md.research.elamur.ai/free/en/papers/carlini-2023-aligned-neural-networks-adversarially-aligned/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.*2023 · 157 citations*
33. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks arXiv:2406.18403**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 141 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/)
34. [**Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models arXiv:2404.18796**Pat Verga, Sebastian Hofstatter, Sophia Althammer, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/verga-2024-replacing-judges-juries-evaluating-llm/)
35. [**Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V arXiv:2310.11441**Jianwei Yang, Hao Zhang, Feng Li, et al.*2023 · 137 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-set-mark-prompting-unleashes-extraordinary/)
36. **[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*
37. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
38. **[Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/wu-2024-janus-decoupling-visual-encoding/) [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/)**Chengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.*2024 · 112 citations*
39. [**JudgeBench: A Benchmark for Evaluating LLM-based Judges arXiv:2410.12784**Sijun Tan, Siyuan Zhuang, Kyle Montgomery, et al.*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-judgebench-benchmark-evaluating-llm-based/)
40. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model arXiv:2401.16420**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
41. **[LVBench: An Extreme Long Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-lvbench-extreme-long-video-understanding/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Weihan Wang, Zehai He, Wenyi Hong, et al.*2024 · 89 citations*
42. [**InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition arXiv:2309.15112**Pan Zhang, Xiaoyi Dong, Bin Wang, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-internlm-xcomposer-vision-language/)
43. **[Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment](https://md.research.elamur.ai/free/en/papers/raina-2024-is-llm-as-judge-robust/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Vyas Raina, Adian Liusie, Mark Gales*2024 · 86 citations*
44. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
45. **[Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-Judge](https://md.research.elamur.ai/free/en/papers/shi-2025-judging-judges-systematic-study-position/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Lin Shi, Chiyu Ma, Wenhua Liang, et al.*2025 · 71 citations*
46. [**CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation arXiv:2311.18702**Pei Ke, Bosi Wen, Zhuoer Feng, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/ke-2023-critiquellm-informative-critique-generation/)
47. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
48. **[OffsetBias: Leveraging Debiased Data for Tuning Evaluators](https://md.research.elamur.ai/free/en/papers/park-2024-offsetbias-leveraging-debiased-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junsoo Park, Seungyeon Jwa, Ren Meiying, et al.*2024 · 67 citations*
49. [**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/)
50. [**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/)
51. **[The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs](https://md.research.elamur.ai/free/en/papers/calderon-2025-alternative-annotator-test-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nitay Calderon, Roi Reichart, Rotem Dror*2025 · 52 citations*
52. [**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/)
53. **[CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists](https://md.research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yukyung Lee, JoongHoon Kim, Jaehee Kim, et al.*2025 · 37 citations*
54. **[The Hidden Attention of Mamba Models](https://md.research.elamur.ai/free/en/papers/ali-2025-hidden-attention-mamba-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ameen Ali Ali, Itamar Zimerman, Lior Wolf*2025 · 32 citations*
55. **[ArAIEval Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal Arabic Content](https://md.research.elamur.ai/free/en/papers/hasanain-2024-araieval-shared-task-propagandistic-techniques/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Maram Hasanain, Md. Arid Hasan, Fatema Ahmad, et al.*2024 · 32 citations*
56. **[MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval](https://md.research.elamur.ai/free/en/papers/zhou-2025-megapairs-massive-data-synthesis-universal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junjie Zhou, Yongping Xiong, Zheng Liu, et al.*2025 · 26 citations*
57. **[CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward](https://md.research.elamur.ai/free/en/papers/liu-2025-compassverifier-unified-robust-verifier-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shudong Liu, Hongwei Liu, Junnan Liu, et al.*2025 · 16 citations*
58. **[CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges](https://md.research.elamur.ai/free/en/papers/li-2025-calibraeval-calibrating-prediction-distribution-mitigate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haitao Li, Junjie Chen, Qingyao Ai, et al.*2025 · 15 citations*
59. **[A Survey on Efficient Large Language Model Training: From Data-centric Perspectives](https://md.research.elamur.ai/free/en/papers/luo-2025-survey-efficient-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyu Luo, Bohan Wu, Xiao Luo, et al.*2025 · 14 citations*
60. **[CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks](https://md.research.elamur.ai/free/en/papers/jiang-2026-codejudgebench-benchmarking-llm-as-judge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongchao Jiang, Yiming Chen, Yushi Cao, et al.*2026 · 13 citations*
61. [**Retrieval-augmented Multi-modal Chain-of-Thoughts Reasoning for Large Language Models arXiv:2312.01714**Bingshuai Liu, Chenyang Lyu, Zijun Min, et al.*2023 · 13 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-retrieval-augmented-multi-modal-chain/)
62. **[Beyond the Surface: Measuring Self-Preference in LLM Judgments](https://md.research.elamur.ai/free/en/papers/chen-2025-beyond-surface-measuring-self-preference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhi-Yuan Chen, Hao Wang, Xinyu Zhang, et al.*2025 · 10 citations*
63. **[Can Many-Shot In-Context Learning Help LLMs as Evaluators? A Preliminary Empirical Study](https://md.research.elamur.ai/free/en/papers/song-2025-can-many-shot-context-learning/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Mingyang Song, Mao Zheng, Xuan Luo*2025 · 9 citations*
64. **[Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-sentient-agent-as-judge-evaluating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bang Zhang, Ruotian Ma, Qingxuan Jiang, et al.*2026 · 6 citations*
65. **[Collaborative Multi-Agent Scripts Generation for Enhancing Imperfect-Information Reasoning in Murder Mystery Games](https://md.research.elamur.ai/free/en/papers/zhong-2026-collaborative-multi-agent-scripts-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Keyang Zhong, Junlin Xie, Hefeng Wu, et al.*2026 · 5 citations*
66. **[Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation](https://md.research.elamur.ai/free/en/papers/moon-2026-don-t-judge-code-its/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiwon Moon, Yerin Hwang, Dongryeol Lee, et al.*2026 · 5 citations*
67. **[How Long Reasoning Chains Influence LLMs' Judgment of Answer Factuality](https://md.research.elamur.ai/free/en/papers/tu-2026-how-long-reasoning-chains-influence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minzhu Tu, Shiyu Ni, Keping Bi*2026 · 3 citations*
68. **[MMCLIP: Cross-Modal Attention Masked Modelling for Medical Language-Image Pre-Training](https://md.research.elamur.ai/free/en/papers/wu-2026-mmclip-cross-modal-attention-masked/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Biao Wu, Yutong Xie, Zeyu Zhang, et al.*2026 · 3 citations*
69. **[CLTL at ArAIEval Shared Task: Multimodal Propagandistic Memes Classification Using Transformer Models](https://md.research.elamur.ai/free/en/papers/wang-2024-cltl-araieval-shared-task-multimodal/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Yeshan Wang, Ilia Markov*2024 · 3 citations*
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