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Yukun Yan

Yukun Yan has 5 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Zhenghao Liu, Ge Yu, Shuo Wang.

5 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 5 · 42 works · 64 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 26 times in our library · 4 more in our library without a page yet · ⭐ Paper Stars ranking: #8090

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

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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework (2025 · 34 citations)
    Testing RAG systems in specialised fields such as law, finance or medicine is hard. Building expert-annotated, domain-specific test sets is expensive and raises privacy issues, and lexical metrics like BLEU or ROUGE-L judge long answers poorly. RAGEval addresses this by generating evaluation data automatically.…
  2. Long-Chain Reasoning Distillation via Adaptive Prefix Alignment (2026 · 3 citations)
    Small student models often learn poorly from the long, reflective chain-of-thought traces that reasoning models such as DeepSeek-R1 produce.
  3. ThinkNote: Enhancing Knowledge Integration and Utilization of Large Language Models via Constructivist Cognition Modeling (2026 · 2 citations)
    LLMs often struggle to use retrieved external knowledge reliably. Noisy, incomplete or unfamiliar evidence can produce inconsistent answers and hallucinations. ThinkNote addresses this by treating the model as an active builder of knowledge rather than a passive reader of context, drawing on constructivist learning…
  4. Enhancing Long-Chain Reasoning Distillation through Error-Aware Self-Reflection (2026 · 1 citation)
    Distilling long Chain-of-Thought (CoT) traces from strong reasoning models into small models often works poorly.
  5. Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling (2026)
    LLM-based evaluators ("LLM-as-a-Judge") tend to rate their own outputs, or outputs resembling their style, more favorably.

All works

9 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them.

  1. MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetHaidong Xin et al.2026
  2. Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetYuqi Xiong et al.2026
  3. CheckRLM: Effective Knowledge–Thought Coherence Checking in Retrieval-Augmented Reasoning ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetDingling Xu et al.2026

 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 26 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

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