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Yuchen Li

Yuchen Li has 4 papers in our library, in 2026, most of them on Language models & pretraining, Reasoning, Bias, fairness & safety; often with Chenyang Lu, Daiting Shi, Dawei Yin.

4 papers in our library · 2026

OpenAlex · h-index 2 · 7 works · 10 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 24 times in our library · ⭐ Paper Stars ranking: #8609

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. 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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability (2026 · 18 citations)
    LLM-based listwise rerankers struggle with complex search needs, such as expert StackExchange questions, coding, or math, because they are mostly trained on web search data like MSMARCO.
  2. Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression (2026 · 8 citations)
    The paper asks why safety-aligned LLMs still give in to jailbreaks. The authors propose that alignment learns refusal mostly from surface token patterns, so a harmful request with the same meaning but an unfamiliar form can slip past safeguards. To test this, they present LogiBreak, a black-box attack that rewrites a…
  3. UniCreative: Unifying Long-form Logic and Short-form Sparkle via Reference-Free Reinforcement Learning (2026 · 1 citation)
    LLM creative writing faces two opposite problems. Long stories and scripts need global planning, or they drift off topic, repeat themselves and lose structure. Short pieces such as poems, slogans or blessings get worse when forced through rigid outlines, and models already tend toward bland, high-probability wording.…
  4. On the Representation Geometry of LoRA Model Merging (2026)
    Combining several task-specific LoRA adapters into one model without further training is hard because their low-rank updates tend to occupy misaligned subspaces.

 Co-authors here

12 of 24 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 24 times (of the 149,439 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

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