Elamur Research⌕
☰
home / authors / Yin Zhang

Yin Zhang

Yin Zhang has 7 papers in our library, in 2021–2026, most of them on Language models & pretraining, Reasoning, Efficient models & compression; often with Chenglin Li, Qianglong Chen, Hengwei Liu.

7 papers in our library · 2021–2026

OpenAlex · ORCID · h-index 16 · 80 works · 974 citations OpenAlex, 2026-10-14

📄 7 works in our library · 🔗 Cited 141 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #6730

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

🎓Zhejiang UniversityHangzhou · China2009–2026 · 53 paperscurrent🎓Shanghai Innovation InstituteShanghai · China2026 · 1 papercurrent🔬Academy of Military Medical SciencesBeijing · China2023–2024 · 3 papers🎓Texas A&M UniversityCollege Station · United States2020–2021 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 11 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 7 worksComputer Science · 7 worksArtificial Intelligence · 7 worksLanguage and Linguistics · 7 worksComputer Vision and Pattern Recognition · 2 worksInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Reasoning · 4 worksLanguage models & pretraining · 4 worksEfficient models & compression · 1 work

 Works by year

2020s

20263 papers20241 paper20231 paper20221 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding (2022 · 40 citations)
    Most document pre-training models treat layout as a 2D extension of 1D positions and serialize OCR output in raster-scan order (top-to-bottom, left-to-right).
  2. KACE: Generating Knowledge Aware Contrastive Explanations for Natural Language Inference (2021 · 28 citations)
    Most explanation generators in NLP only justify the chosen label ("why A"). This paper argues that contrastive explanations ("why A and not B") are more useful, both for users and for the model. KACE is a post-hoc framework for natural language inference built from three stages:
  3. Teaching Small Language Models Reasoning through Counterfactual Distillation (2024 · 21 citations)
    The paper addresses a weakness of chain-of-thought (CoT) distillation, where a large teacher model's rationales are used to fine-tune small language models (SLMs).
  4. Mixed Distillation Helps Smaller Language Model Better Reasoning (2023 · 11 citations)
    Large language models reason well but are expensive to run. Earlier work on distilling reasoning into compact models mostly transfers only natural-language Chain of Thought (CoT). This paper argues that Program of Thought (PoT), where the model writes executable Python, is a valuable extra training signal. The…
  5. VideoPro: Adaptive Program Reasoning for Long Video Understanding (2026 · 6 citations)
    Long videos are hard for VideoLLMs because the visual cues needed to answer a question are few and scattered across a long timeline.
  6. AutoTaskEval: Towards Domain-Specific and Fine-Grained Evaluation for LLMs (2026)
    Static, manually built benchmarks are expensive, cover few tasks, and lose discriminative power as LLMs improve.
  7. Leveraging Outline-Optimized Generative Interactions and Critique for Self-Refining Outlines with Reinforcement Learning (2026)
    Small language models struggle to produce hierarchical outlines for Wikipedia-style expository articles. Their outlines tend to skip levels, omit important branches and distribute depth poorly. Existing remedies such as STORM, OmniThink or RAPID rely on costly multi-turn LLM interaction or fixed refinement…

All works

9 works of theirs in our library, the most cited first; 7 with a page here, the others link their original until we summarise them.

  1. Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetYun He et al.2020 · 128 citations
  2. ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document UnderstandingarXiv:2210.06155Qiming Peng, Yinxu Pan, Wenjin Wang, et al.2022 · 40 citations
  3. KACE: Generating Knowledge Aware Contrastive Explanations for Natural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Qianglong Chen, Feng Ji, Xiangji Zeng, et al.2021 · 28 citations
  4. PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetYun He et al.2020 · 25 citations
  5. Teaching Small Language Models Reasoning through Counterfactual DistillationConference on Empirical Methods in Natural Language Processing (EMNLP)Tao Feng, Yicheng Li, Chenglin Li, et al.2024 · 21 citations
  6. Mixed Distillation Helps Smaller Language Model Better ReasoningarXiv:2312.10730Chenglin Li, Qianglong Chen, Liangyue Li, et al.2023 · 11 citations
  7. VideoPro: Adaptive Program Reasoning for Long Video UnderstandingAnnual Meeting of the Association for Computational Linguistics (ACL)Chenglin Li, Feng Han, Yikun Wang, et al.2026 · 6 citations
  8. AutoTaskEval: Towards Domain-Specific and Fine-Grained Evaluation for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Qingqing Lyu, Linjuan Wu, Yongliang Shen, et al.2026
  9. Leveraging Outline-Optimized Generative Interactions and Critique for Self-Refining Outlines with Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Hengwei Liu, Haoyuan Ma, Qingqing Lyu, et al.2026

 Co-authors here

12 of 30 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 141 times (of the 149,439 papers whose bibliographies we read); 25 citing papers with a page here →.

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/yin-zhang/