---
title: "Who cites Erin Bransom — 298 papers of our library"
description: "298 papers of the Elamur Research library cite the works of Erin Bransom, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/erin-bransom/cited-by/"
---
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# Who cites Erin Bransom

301 citations of their works from 298 papers of our library (of the 149,439 whose bibliographies we read) · 60 with a page here, the most cited first · [← Erin Bransom](https://md.research.elamur.ai/free/en/authors/erin-bransom/)

1. [**Qwen2.5-VL Technical Report arXiv:2502.13923**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 1,031 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
2. **[FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 987 citations*
3. [**Qwen3-VL Technical Report arXiv:2511.21631**Shuai Bai, Yuxuan Cai, Ruizhe Chen, et al.*2025 · 370 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen3-vl-technical-report/)
4. [**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/)
5. [**Fine-Grained Human Feedback Gives Better Rewards for Language Model Training arXiv:2306.01693**Zeqiu Wu, Yushi Hu, Weijia Shi, et al.*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fine-grained-human-feedback-gives/)
6. [**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/)
7. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
8. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
9. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding arXiv:2412.10302**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
10. **[Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models](https://md.research.elamur.ai/free/en/papers/shao-2024-assisting-writing-wikipedia-like-articles/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yijia Shao, Yucheng Jiang, Theodore Kanell, et al.*2024 · 131 citations*
11. [**BooookScore: A systematic exploration of book-length summarization in the era of LLMs arXiv:2310.00785**Yapei Chang, Kyle Lo, Tanya Goyal, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-booookscore-systematic-exploration-book-length/)
12. [**Pixtral 12B arXiv:2410.07073**Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-pixtral-12b/)
13. [**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/)
14. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
15. [**PaperBench: Evaluating AI's Ability to Replicate AI Research arXiv:2504.01848**Giulio Starace, Oliver Jaffe, Dane Sherburn, et al.*2025 · 86 citations*](https://md.research.elamur.ai/free/en/papers/starace-2025-paperbench-evaluating-ai-s/)
16. [**MARG: Multi-Agent Review Generation for Scientific Papers arXiv:2401.04259**Mike D'Arcy, Tom Hope, Larry Birnbaum, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/arcy-2024-marg-multi-agent-review/)
17. **[Is LLM a Reliable Reviewer? A Comprehensive Evaluation of LLM on Automatic Paper Reviewing Tasks](https://md.research.elamur.ai/free/en/papers/zhou-2024-is-llm-reliable-reviewer-comprehensive/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ruiyang Zhou, Lu Chen, Kai Yu*2024 · 74 citations*
18. **[Summary of a Haystack: A Challenge to Long-Context LLMs and RAG Systems](https://md.research.elamur.ai/free/en/papers/laban-2024-summary-haystack-challenge-long-context/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Philippe Laban, Alexander Fabbri, Caiming Xiong, et al.*2024 · 69 citations*
19. [**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/)
20. **[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*
21. **[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*
22. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
23. [**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/)
24. [**The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input arXiv:2501.03200**Alon Jacovi, Andrew Wang, Chris Alberti, et al.*2025 · 32 citations*](https://md.research.elamur.ai/free/en/papers/jacovi-2025-facts-grounding-leaderboard-benchmarking-llms/)
25. **[Reading Subtext: Evaluating Large Language Models on Short Story Summarization with Writers](https://md.research.elamur.ai/free/en/papers/subbiah-2024-reading-subtext-evaluating-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Melanie Subbiah, Sean Zhang, Lydia B. Chilton, et al.*2024 · 30 citations*
26. **[Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation](https://md.research.elamur.ai/free/en/papers/eger-2025-transforming-science-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Steffen Eger, Yong Cao, Jennifer D'Souza, et al.*2025 · 25 citations*
27. **[A Survey on Evaluation of LLM-based Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-survey-evaluation-llm-based-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaf Yehudai, Lilach Eden, Alan Li, et al.*2026 · 21 citations*
28. **[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*
29. **[KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding](https://md.research.elamur.ai/free/en/papers/heakl-2025-kitab-bench-comprehensive-multi-domain/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ahmed Heakl, Muhammad Abdullah Sohail, Mukul Ranjan, et al.*2025 · 21 citations*
30. [**Sparks of Science: Hypothesis Generation Using Structured Paper Data arXiv:2504.12976**Charles O'Neill, Tirthankar Ghosal, Roberta R\uaileanu, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/o-neill-2025-sparks-science-hypothesis-generation-using/)
31. **[Literature Meets Data: A Synergistic Approach to Hypothesis Generation](https://md.research.elamur.ai/free/en/papers/liu-2025-literature-meets-data-synergistic-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haokun Liu, Yangqiaoyu Zhou, Mingxuan Li, et al.*2025 · 12 citations*
32. [**Fanar 2.0: Arabic Generative AI Stack arXiv:2603.16397**FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad, et al.*2026 · 11 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-fanar-2-0-arabic-generative/)
33. [**AIN: The Arabic INclusive Large Multimodal Model arXiv:2502.00094**Ahmed Heakl, Sara Ghaboura, Omkar Thawkar, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/heakl-2025-ain-arabic-inclusive-large-multimodal/)
34. **[Grounding Multilingual Multimodal LLMs With Cultural Knowledge](https://md.research.elamur.ai/free/en/papers/nyandwi-2025-grounding-multilingual-multimodal-llms-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jean De Dieu Nyandwi, Yueqi Song, Simran Khanuja, et al.*2025 · 11 citations*
35. **[InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning and Reflection](https://md.research.elamur.ai/free/en/papers/liu-2026-infiguiagent-multimodal-generalist-gui-agent/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuhang Liu, Pengxiang Li, Zishu Wei, et al.*2026 · 10 citations*
36. [**Usefulness of LLMs as an Author Checklist Assistant for Scientific Papers: NeurIPS'24 Experiment arXiv:2411.03417**Alexander Goldberg, Ihsan Ullah, Thanh Gia Hieu Khuong, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/goldberg-2024-usefulness-llms-author-checklist-assistant/)
37. **[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*
38. **[Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization](https://md.research.elamur.ai/free/en/papers/zhong-2025-discourse-driven-evaluation-unveiling-factual/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yang Zhong, Diane Litman*2025 · 8 citations*
39. **[Stress Testing Factual Consistency Metrics for Long-Document Summarization](https://md.research.elamur.ai/free/en/papers/mujahid-2026-stress-testing-factual-consistency-metrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zain Muhammad Mujahid, Dustin Wright, Isabelle Augenstein*2026 · 3 citations*
40. **[Author-in-the-Loop Response Generation and Evaluation: Integrating Author Expertise and Intent in Responses to Peer Review](https://md.research.elamur.ai/free/en/papers/ruan-2026-author-loop-response-generation-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Ruan, Iryna Gurevych*2026 · 2 citations*
41. **[NSF-SciFy: Mining the NSF Awards Database for Scientific Claims](https://md.research.elamur.ai/free/en/papers/rao-2026-nsf-scify-mining-nsf-awards/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Delip Rao, Weiqiu You, Eric Wong, et al.*2026 · 2 citations*
42. **[RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation](https://md.research.elamur.ai/free/en/papers/wu-2026-rbtact-rebuttal-as-supervision-actionable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sihong Wu, Yiling Ma, Yilun Zhao, et al.*2026 · 2 citations*
43. [**STEP3-VL-10B Technical Report arXiv:2601.09668**Ailin Huang, Chengyuan Yao, Chunrui Han, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/huang-2026-step3-vl-10b-technical/)
44. **[When Seeing Overrides Knowing: Disentangling Knowledge Conflicts in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/ortu-2026-when-seeing-overrides-knowing-disentangling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Francesco Ortu, Zhijing Jin, Diego Doimo, et al.*2026 · 2 citations*
45. [**Benchmarking Vision Language Models on German Factual Data arXiv:2504.11108**Rene Peinl, Vincent Tischler*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/peinl-2025-benchmarking-vision-language-models-german/)
46. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation*
47. **[Intention-Adaptive LLM Fine-Tuning for Text Revision Generation](https://md.research.elamur.ai/free/en/papers/liu-2026-intention-adaptive-llm-fine-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhexiong Liu, Diane Litman*2026 · 1 citation*
48. **[RotBench: Evaluating Multi-modal Large Language Models on Identifying Image Rotation](https://md.research.elamur.ai/free/en/papers/niu-2026-rotbench-evaluating-multi-modal-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin, et al.*2026 · 1 citation*
49. **[Adapting Vision-Language Models for E-commerce Understanding at Scale](https://md.research.elamur.ai/free/en/papers/nulli-2026-adapting-vision-language-models-e/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Matteo Nulli, Vladimir Orshulevich, Tala Bazazo, et al.*2026*
50. **[Agentic Oversight via Dialectic Reasoning](https://md.research.elamur.ai/free/en/papers/ranaldi-2026-agentic-oversight-dialectic-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leonardo Ranaldi, Federico Ranaldi*2026*
51. **[Bears, all bears, and some bears. Language Constraints on Language Models' Inductive Inferences](https://md.research.elamur.ai/free/en/papers/padmanabhan-2026-bears-all-bears-some-bears/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sriram Padmanabhan, Siyuan Song, Kanishka Misra*2026*
52. **[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*
53. **[Cross-Modal Taxonomic Generalization in (Vision-) Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-cross-modal-taxonomic-generalization-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyang Xu, Marcelo Sandoval-Castañeda, Karen Livescu, et al.*2026*
54. **[GeoRC: A Benchmark for Geolocation Reasoning Chains](https://md.research.elamur.ai/free/en/papers/talreja-2026-georc-benchmark-geolocation-reasoning-chains/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohit Talreja, Joshua Diao, Jim James, et al.*2026*
55. **[Grounded Concreteness: Human-Like Concreteness Sensitivity in Vision–Language Models](https://md.research.elamur.ai/free/en/papers/roy-2026-grounded-concreteness-human-like-concreteness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Aryan Roy, Zekun Wang, Christopher J. MacLellan*2026*
56. **[How effective are VLMs in assisting humans in inferring the quality of mental models from Multimodal short answers?](https://md.research.elamur.ai/free/en/papers/sil-2026-how-effective-are-vlms-assisting/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Pritam Sil, Durgaprasad Karnam, Vinay Reddy Venumuddala, et al.*2026*
57. **[Revisiting Faithfulness Annotations for Long-form Summaries](https://md.research.elamur.ai/free/en/papers/zhong-2026-revisiting-faithfulness-annotations-long-form/) [Linguistic Annotation Workshop (LAW)](https://md.research.elamur.ai/free/en/venues/law/)**Yang Zhong, Yang Janet Liu, Diane Litman*2026*
58. **[TURTLEAI: Benchmarking Multimodal Models for Visual Programming in Turtle Graphics](https://md.research.elamur.ai/free/en/papers/wen-2026-turtleai-benchmarking-multimodal-models-visual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Wen, Jacqueline Staub, Adish Singla*2026*
59. **[VIGiA: Instructional Video Guidance via Dialogue Reasoning and Retrieval](https://md.research.elamur.ai/free/en/papers/silva-2026-vigia-instructional-video-guidance-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Diogo Glória-Silva, David Semedo, Joao Magalhaes*2026*
60. **[When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise](https://md.research.elamur.ai/free/en/papers/shin-2026-when-relations-break-analyzing-relation/) [Workshop on Advances in Language and Vision Research (ALVR)](https://md.research.elamur.ai/free/en/venues/alvr/)**Philip Wootaek Shin, Ajay Narayanan Sridhar, Lakshmi Sivani Devarapalli, et al.*2026*

238 more citing papers of our library have no page here yet.

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