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Zhining Liu

Zhining Liu has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Dialogue systems, Vision & language; often with Hanghang Tong, Tianxin Wei, Jingrui He.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 9 · 34 works · 244 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 13 times in our library · ⭐ Paper Stars ranking: #9313

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

🏢HyPerCompWestlake Village · United States2001–2026 · 7 paperscurrent🎓Louisiana Tech UniversityRuston · United States1996–1998 · 8 papers🏢HyPerComp EngineeringBrigham City · United States2005–2025 · 5 papers🎓University of Colorado DenverDenver · United States1994–1997 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 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 3Research subjects and languages the work is about.Language models & pretraining · 1 workDialogue systems · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence (2025 · 11 citations)
    Supplying a language model with evidence passages, whether retrieved or user-provided, should make its answers better grounded.
  2. Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents (2026 · 6 citations)
    Agents built on multimodal large language models (MLLMs) need to remember what users show and tell them over many conversations.

 Co-authors here

8 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 13 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated

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