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Haizhou Shi

Haizhou Shi has 2 papers in our library, in 2024–2025, most of them on Information retrieval & search, Vision & language; often with Akshay Nambi, Boci Peng, Hao Wang.

2 papers in our library · 2024–2025

OpenAlex · ORCID · h-index 11 · 26 works · 539 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 125 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #4983

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

🎓Rutgers, The State University of New JerseyNew Brunswick · United States2023–2025 · 13 paperscurrent🎓Zhejiang UniversityHangzhou · China2019–2023 · 10 papers

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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 2Research subjects and languages the work is about.Information retrieval & search · 1 workVision & language · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Retrieval-augmented generation · 1 work

 Works by year

2020s

20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Graph Retrieval-Augmented Generation: A Survey (2024 · 276 citations)
    Standard Retrieval-Augmented Generation (RAG) supplies LLMs with external text so they hallucinate less and can use domain-specific or current knowledge.
  2. Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models (2025 · 21 citations)
    Evaluations of multimodal large language models (MLLMs) usually involve one or a few images, or rely on too few test cases to be statistically meaningful.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Graph Retrieval-Augmented Generation: A SurveyACM Transactions on Information SystemsBoci Peng, Yun Zhu, Yongchao Liu, et al.2024 · 276 citations
  2. CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction ↗Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yetTao Chen et al.2021 · 71 citations
  3. Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hengyi Wang, Haizhou Shi, Shiwei Tan, et al.2025 · 21 citations

 Co-authors here

7 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 125 times (of the 149,439 papers whose bibliographies we read); 26 citing papers with a page here →.

Updated

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