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Tian Xueyun

Tian Xueyun has 3 papers in our library, in 2026, most of them on Reasoning, Vision & language; often with Bingbing Xu, Huawei Shen, Heng Dong.

3 papers in our library · 2026

OpenAlex · h-index 1 · 11 works · 1 citations OpenAlex, 2026-10-14

📄 3 works in our library · ⭐ Paper Stars ranking: #13369

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

🎓University of Chinese Academy of SciencesBeijing · China2026 · 3 paperscurrent🔬Institute of Computing TechnologyBeijing · China2026 · 2 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.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 workSocial Sciences · 1 workSociology and Political Science · 1 work

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

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Chain-of-Memory: Lightweight Memory Construction with Dynamic Evolution for LLM Agents (2026)
    LLM agents handling long interaction histories rely on external memory. Popular systems spend heavily on turning past dialogue into trees or graphs, then simply paste retrieved snippets into the prompt. The authors show that this costly structuring barely beats plain RAG. They also find that retrieving the right…
  2. Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization (2026)
    SFT on distilled chain-of-thought data usually relies on rejection sampling, which keeps only trajectories whose final answer is correct.
  3. ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding (2026)
    ROMA tackles streaming audio-video understanding: an assistant must watch and listen to a live stream, answer questions when asked (reactive mode), and speak up unprompted when something relevant happens (proactive mode).

 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.

Updated

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