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Xintong Li

Xintong Li has 3 papers in our library, in 2025–2026, most of them on Reasoning, Vision & language, Efficient models & compression; often with Junda Wu, Branislav Kveton, Chengkai Huang.

3 papers in our library · 2025–2026

OpenAlex · h-index 0 · 4 works · 0 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 10 times in our library · ⭐ Paper Stars ranking: #8932

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

🏢AppleCupertino · United States2026 · 1 papercurrent🎓Shanghai Jiao Tong UniversityShanghai · China2026 · 1 papercurrent🎓University of California San DiegoSan Diego · United States2026 · 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 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksDecision Sciences · 1 workManagement Science and Operations Research · 1 workComputer Vision and Pattern Recognition · 1 workSignal Processing · 1 work

🧭 Topics 3Research subjects and languages the work is about.Efficient models & compression · 1 workReasoning · 1 workVision & language · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. From Selection to Generation: A Survey of LLM-based Active Learning (2025 · 22 citations)
    Active learning (AL) traditionally lowers labeling effort by picking the most useful unlabeled examples with metrics such as uncertainty or diversity.
  2. MelTrim: Coarse-to-Fine Data Pruning for Speech Classification (2026)
    Data pruning, which means selecting a small coreset that trains models nearly as well as the full dataset, has been studied mostly for images and text.
  3. SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes (2026)
    Multimodal LLMs often produce rationales that sound convincing but are not tied to what the image actually shows.

 Co-authors here

12 of 18 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 10 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated

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