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Yujie Luo

Yujie Luo has 3 papers in our library, in 2025–2026, most of them on Knowledge graphs & ontologies, Efficient models & compression; often with Huajun Chen, Lun Du, Ningyu Zhang.

3 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 12 · 43 works · 373 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 47 times in our library · ⭐ Paper Stars ranking: #7747

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

🎓Chongqing UniversityChongqing · China2019–2026 · 9 paperscurrent🎓University of MinnesotaMinneapolis · United States2020–2026 · 7 paperscurrent🏢Ant GroupHangzhou · China2025–2026 · 3 paperscurrent🎓Zhejiang UniversityHangzhou · China2025–2026 · 3 paperscurrent🎓Beijing Jiaotong UniversityBeijing · China2026 · 1 papercurrent🏛️Chinese Academy of SciencesBeijing · China2024–2025 · 2 papers🔬Institute of Rock and Soil MechanicsWuhan · China2024–2025 · 2 papers🔬State Key Laboratory of Geomechanics and Geotechnical EngineeringWuhan · China2024–2025 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 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 8The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArts and Humanities · 2 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workDecision Sciences · 1 workInformation Systems · 1 workInformation Systems and Management · 1 work

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 1 workKnowledge graphs & ontologies · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. LightThinker: Thinking Step-by-Step Compression (2025 · 50 citations)
    Slow, o1-style reasoning makes LLMs produce very long token sequences. Because attention cost grows quadratically and the KV Cache grows linearly with context, these outputs are expensive in memory and time. LightThinker addresses this by teaching a model to condense each intermediate reasoning step as it goes. After…
  2. Can We Predict Before Executing Machine Learning Agents? (2026 · 2 citations)
    ML agents usually improve their code through repeated generate-execute-feedback cycles. Every candidate has to be trained and run, so a single MLE-Bench run can take many hours. The authors ask whether an LLM can act as an implicit world model and judge which solution will perform better before any code runs. They…
  3. What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations (2026)
    LLM agents that try to reproduce AI papers often fail to produce working code. Papers leave out implementation specifics, and standard RAG does not recover technical details buried in cited works or the code signals in related repositories. The authors propose Executable Knowledge Graphs (xKG), a plug-in knowledge…

 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 47 times (of the 149,439 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated

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