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Mingyang Chen

Mingyang Chen has 5 papers in our library, in 2023–2026, most of them on Language models & pretraining, Efficient models & compression; often with Fan Yang, Tianpeng Li, Chenzheng Zhu.

5 papers in our library · 2023–2026

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

📄 5 works in our library · 🔗 Cited 59 times in our library · ⭐ Paper Stars ranking: #6897

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

🏢BaichuanBeijing · China2026 · 3 paperscurrent

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 9The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksArtificial Intelligence · 5 worksArts and Humanities · 4 worksLanguage and Linguistics · 4 worksMedicine · 1 workComputer Vision and Pattern Recognition · 2 worksHealth Informatics · 1 workControl and Systems Engineering · 1 workEngineering · 1 work

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers20251 paper20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Lion: Adversarial Distillation of Proprietary Large Language Models (2023 · 70 citations)
    Distilling a closed, API-only LLM into a small open model has usually been one-directional. The student is fine-tuned to copy the teacher's answers on a fixed instruction set and gets no signal about where it is still weak. Jiang et al. adapt adversarial knowledge distillation to this black-box setting. The teacher's…
  2. Baichuan-M2: Scaling Medical Capability with Large Verifier System (2025 · 19 citations)
    Medical LLMs often do well on exam-style tests such as USMLE but less well in real consultations, where information comes in gradually over many turns and communication matters.
  3. Baichuan Alignment Technical Report (2024 · 5 citations)
    Alignment methods for large language models are usually kept proprietary or described only in fragments. This technical report from Baichuan Inc. and Peking University sets out the full alignment pipeline behind the Baichuan models. The pipeline has three stages. A Prompt Augmentation System (PAS) automatically…
  4. NCL&HKU-NarrSim at SemEval-2026 Task 4: Aspect-Based Agents and Supervised Contrastive Embeddings for Narrative Similarity (2026 · 1 citation)
    This paper presents the NCL&HKU-NarrSim system for SemEval-2026 Task 4. The task asks which of two candidate stories is narratively closer to an anchor story, judged on deeper structure rather than shared wording. The authors propose one approach per track.
  5. Training Verifier to Assessing Complex Real-World Tool-Use Trajectories (2026)
    LLM agents that handle multi-turn customer-service style tasks need training dialogues that reflect real user–agent collaboration.

 Co-authors here

12 of 26 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 59 times (of the 149,439 papers whose bibliographies we read); 17 citing papers with a page here →.

Updated

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