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Yangshijie Zhang

Yangshijie Zhang has 4 papers in our library, in 2026, most of them on Language models & pretraining, Reasoning; often with Bin-Bin Yang, ChenZhuo Zhao, Feng Xiao.

4 papers in our library · 2026

OpenAlex · ORCID · h-index 3 · 7 works · 28 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 3 times in our library · ⭐ Paper Stars ranking: #10821

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

🎓Lanzhou UniversityLanzhou · China2026 · 2 paperscurrent🎓Istituto Universitario di Studi Superiori di PaviaPavia · Italy2024–2025 · 2 papers🎓University of TurinTurin · Italy2024–2025 · 2 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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 works

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 1 work

 Works by year

2020s

20264 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Incomplete In-context Learning (2026 · 2 citations)
    Standard in-context learning assumes that the retrieval pool has demonstrations for every output label. This paper drops that assumption. It studies cases where some classes have no labeled examples, for instance because the database is outdated, classes are highly imbalanced, or annotation follows a…
  2. EvolvR: Self-Evolving Pairwise Reasoning for Story Evaluation to Enhance Generation (2026 · 1 citation)
    LLM judges remain weak at assessing stories. Prompting closed models is brittle, and fine-tuned open evaluators usually output scores without explicit reasoning. The authors propose EvolvR, a framework that teaches an open-source evaluator to reason over pairs of stories. The model works aspect by aspect, for example…
  3. Task-Related In-Context Learning (2026)
    Conventional in-context learning (ICL) presumes that the retrieval pool and the test set use the same label inventory.
  4. Triviality Corrected Endogenous Reward (2026)
    Reinforcement fine-tuning for open-ended writing lacks verifiable rewards. It usually depends on costly proprietary LLM judges or on judge models trained with annotated preference data. The authors ask whether confidence-based endogenous rewards, which work for unsupervised RL in math, can serve writing instead. They…

 Co-authors here

12 of 14 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 3 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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