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Hanting Chen

Hanting Chen has 4 papers in our library, in 2023–2026, most of them on Language models & pretraining, Information retrieval & search, Efficient models & compression; often with Kai Han, Yehui Tang, Yunhe Wang.

4 papers in our library · 2023–2026

OpenAlex · h-index 21 · 75 works · 8,177 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 40 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #8720

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

🏢Huawei TechnologiesShenzhen · China2019–2026 · 33 paperscurrent🎓Beihang UniversityBeijing · China2025–2026 · 2 paperscurrent🎓Peking UniversityBeijing · China2018–2022 · 19 papers🎓Chengdu University of Traditional Chinese MedicineChengdu · China2017–2018 · 3 papers

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 5The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksArtificial Intelligence · 4 worksArts and Humanities · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3 worksEfficient models & compression · 1 workInformation retrieval & search · 1 work

 Works by year

2020s

20262 papers20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition (2025 · 13 citations)
    Reasoning-focused LLMs such as DeepSeek-R1 are expensive to deploy because they are very large and generate long chains of thought, sometimes tens of thousands of tokens per problem.
  2. PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation (2023 · 10 citations)
    Progress in large language models has mostly come from adding parameters and data. The design of the Transformer block itself gets little attention, even though large models are costly to run. The authors study LLaMA-style decoders and identify feature collapse: a rank metric shows token representations growing more…
  3. Multi-Granularity Semantic Revision for Large Language Model Distillation (2026 · 2 citations)
    The paper addresses white-box knowledge distillation (KD) for auto-regressive LLMs, where a compact student learns from the full output distributions of a larger teacher.
  4. MATCH: Modulating Attention via In-Context Retrieval for Long-Context Transformers (2026)
    Sparse-attention LLMs, such as models built on sliding windows, save compute and memory. They tend to fail, however, when an answer depends on recalling an exact detail far back in the input. MATCH tackles this by pairing a sparsified Transformer with a lightweight retrieval component that treats the prompt itself as…

All works

6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. Data-Free Learning of Student Networks ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetHanting Chen et al.2019 · 357 citations
  2. Image Processing GNN: Breaking Rigidity in Super-Resolution ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYuchuan Tian et al.2024 · 52 citations
  3. Pangu Embedded: An Efficient Dual-system LLM Reasoner with MetacognitionarXiv:2505.22375Hanting Chen, Yasheng Wang, Kai Han, et al.2025 · 13 citations
  4. PanGu-π: Enhancing Language Model Architectures via Nonlinearity CompensationarXiv:2312.17276Yunhe Wang, Hanting Chen, Yehui Tang, et al.2023 · 10 citations
  5. Multi-Granularity Semantic Revision for Large Language Model DistillationAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Liu, Yun Zhang, Wei Li, et al.2026 · 2 citations
  6. MATCH: Modulating Attention via In-Context Retrieval for Long-Context TransformersAnnual Meeting of the Association for Computational Linguistics (ACL)Linrui Ma, Chun Hei Lo, Xinyu Wang, et al.2026

 Co-authors here

12 of 23 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 40 times (of the 149,439 papers whose bibliographies we read); 10 citing papers with a page here →.

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