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Shengyu Zhang

Shengyu Zhang has 5 papers in our library, in 2023–2026, most of them on Language models & pretraining, Vision & language, Sentiment & emotion; often with Fei Qing Wu, Guoyin Wang, Jiwei Li.

5 papers in our library · 2023–2026

OpenAlex · h-index 0 · 3 works · 0 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 359 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #3632

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Zhejiang UniversityHangzhou · China2026 · 2 paperscurrent🔬Shanghai Advanced Research InstitutePudong · China2026 · 1 papercurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 5 worksComputer Science · 5 worksArtificial Intelligence · 5 worksLanguage and Linguistics · 5 worksComputer Vision and Pattern Recognition · 4 worksGeneral Social Sciences · 1 workSocial Sciences · 1 work

🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 2 worksSentiment & emotion · 1 workVision & language · 2 worksReasoning · 1 workEfficient models & compression · 1 work

 Works by year

2020s

20263 papers20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Instruction Tuning for Large Language Models: A Survey (2023 · 520 citations)
    This survey maps the research on instruction tuning (IT), which the authors treat as the same thing as supervised fine-tuning (SFT).
  2. Sentiment Analysis through LLM Negotiations (2023 · 25 citations)
    Large language models are typically applied to sentiment classification through a single in-context learning (ICL) prompt answered in one pass.
  3. InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning and Reflection (2026 · 10 citations)
    Multimodal-LLM GUI agents often fail to connect an instruction to the right on-screen element or tap location.
  4. Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding (2026)
    GUI grounding means turning a natural-language instruction into exact click coordinates on a screenshot. MLLMs find it hard on high-resolution, crowded interfaces: they often understand the request but miss the precise pixel location. Drawing several samples raises Pass@k. However, clustering-style self-consistency…
  5. RetentiveKV: State-Space Memory for Uncertainty-Aware Multimodal KV Cache Eviction (2026)
    Multimodal LLMs that process long or high-resolution visual inputs accumulate a very large KV cache. Most compression methods evict tokens on the assumption that tokens with low attention now will stay unimportant. The authors argue this assumption fails for images in two ways. Some visual tokens look irrelevant…

All works

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

  1. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  2. Sentiment Analysis through LLM NegotiationsarXiv:2311.01876Xiaofei Sun, Xiaoya Li, Shengyu Zhang, et al.2023 · 25 citations
  3. InfiGUIAgent: A Multimodal Generalist GUI Agent with Native Reasoning and ReflectionConference of the European Chapter of the Association for Computational Linguistics (EACL)Yuhang Liu, Pengxiang Li, Zishu Wei, et al.2026 · 10 citations
  4. Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI GroundingAnnual Meeting of the Association for Computational Linguistics (ACL)Wenkai Wang, Xiyun Li, Hongcan Guo, et al.2026
  5. RetentiveKV: State-Space Memory for Uncertainty-Aware Multimodal KV Cache EvictionFindings of the Association for Computational LinguisticsSihao Liu, YuFan Xiong, Zhonghua Jiang, et al.2026
  6. DAC-Bench: A Decision-Aware Benchmark for Compositional Mobile GUI Tasks ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYuqing Zhang et al.2026

 Co-authors here

12 of 17 co-authors with a page, the most papers together first.

Venues

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

 Cited by

Papers of our library cite their works 359 times (of the 149,439 papers whose bibliographies we read); 71 citing papers with a page here →.

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