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Ang Lv

Ang Lv has 3 papers in our library, in 2026, most of them on Reasoning, Interpretability; often with Rui Yan, Di Wang, Feng Wang.

3 papers in our library · 2026

OpenAlex · ORCID · h-index 4 · 31 works · 53 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 13 times in our library · ⭐ Paper Stars ranking: #10812

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

🎓Renmin University of ChinaBeijing · China2023–2026 · 28 paperscurrent🏢TencentShenzhen · China2024–2025 · 2 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 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 workSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 2Research subjects and languages the work is about.Reasoning · 1 workInterpretability · 1 work

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. StepHint: Multi-level Stepwise Hints Enhance Reinforcement Learning to Reason (2026 · 13 citations)
    Reinforcement learning with verifiable rewards (RLVR) improves LLM reasoning, but it has two weaknesses. The first is the near-miss reward problem: one early slip ruins an otherwise sound solution, so the rollout earns no reward. The second is exploration stagnation: the policy keeps sampling familiar solutions…
  2. Data Pollination: An Emergent Ecological Process Driving AI Population Evolution (2026)
    The paper argues that language models do not evolve in isolation. Their generated text is published online, scraped into web corpora, and used to train later models, often from other organizations. The authors call this unplanned feedback loop "data pollination" and ask how it affects the risk of model collapse under…
  3. Union-of-Experts: Neurons in Mixture-of-Experts are Secretly Routers (2026)
    Standard Mixture-of-Experts (MoE) language models use a separate router that assigns tokens to experts without any knowledge of the experts' weights.

 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); 5 citing papers with a page here →.

Updated

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