🧑‍🔬 Yihao Quan

🏛️ Affiliations

🎓University of South ChinaHengyang · China2024–2026 · 7 paperscurrent🎓Rutgers, The State University of New JerseyNew Brunswick · United States2026 · 4 paperscurrent🎓Shanghai Jiao Tong UniversityShanghai · China2026 · 3 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Shallow Focus, Deep Fixes: Enhancing Shallow Layers Vision Attention Sinks to Alleviate Hallucination in LVLMs (2025 · 14 citations)
   The paper investigates why large vision-language models (LVLMs) hallucinate, focusing on attention over image tokens, which make up most of the input.
2. From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning Tasks (2025 · 12 citations)
   Large vision-language models (LVLMs) turn each image into hundreds of tokens before passing it to an LLM. How those visual tokens actually shape the generated answer has been unclear. The authors study this "information flow", meaning how strongly system, image and user-prompt tokens influence answer tokens, layer by…
3. ART: Attention Replacement Technique to Improve Factuality in LLMs (2026 · 1 citation)
   This paper links hallucination in LLMs to the way attention is distributed in the earliest layers. Inspecting attention maps of shallow layers (e.g., Layer 0 of Qwen2.5-7B-Instruct on a GSM8K sample), the authors group heads into three types. Uniform heads spread weight evenly over the context, local heads look…

All works

5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Shallow Focus, Deep Fixes: Enhancing Shallow Layers Vision Attention Sinks to Alleviate Hallucination in LVLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaofeng Zhang, Yihao Quan, Chen Shen, et al.2025 · 14 citations
2. From Redundancy to Relevance: Information Flow in LVLMs Across Reasoning TasksConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xiaofeng Zhang, Yihao Quan, Chen Shen, et al.2025 · 12 citations
3. Counting Circuits: Mechanistic Interpretability of Visual Reasoning in Large Vision-Language Models ↗arXiv (Cornell University) · no summary yetLiwei Che et al.2026 · 2 citations
4. ART: Attention Replacement Technique to Improve Factuality in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Ziqin Luo, Yihao Quan, Xiaofeng Zhang, et al.2026 · 1 citation
5. Why MLLMs Struggle to Count: Overcoming Individuation and Aggregation Bottlenecks with ConvStack ↗arXiv (Cornell University) · no summary yetLiwei Che et al.2026

🤝 Co-authors here

9 co-authors with a page, the most papers together first.

• Chen Shen ×3
• Xiaofeng Zhang ×3
• Xiaosong Yuan ×3
• Chaochen Gu ×2
• Jieping Ye ×2
• Shaotian Yan ×2
• Hao Cheng
• Hao Tang
• Wenxiao Wang

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
• Conference of the North American Chapter of the Association for Computational Linguistics (NAACL): NAACL 2025

🔗 Cited by

Papers of our library cite their works 18 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

Updated 31 October 2026

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