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Bosi Wen

Bosi Wen has 3 papers in our library, in 2023, most of them on Language models & pretraining, Dialogue systems; often with Jiale Cheng, Pei Ke, Shengyuan Wang.

3 papers in our library · 2023

OpenAlex · h-index 6 · 34 works · 111 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 394 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4650

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.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. AlignBench: Benchmarking Chinese Alignment of Large Language Models (2023 · 73 citations)
    Chinese benchmarks such as C-Eval and CMMLU score exam-style knowledge. They do not show whether an instruction-tuned model handles real user requests well. LLM-as-Judge suites like AlpacaEval and MT-Bench, meanwhile, exist only in English. AlignBench fills this gap with 683 Chinese queries taken mostly from an…
  2. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation (2023 · 68 citations)
    LLM-based evaluators trained on critiques that GPT-4 produces through direct prompting often give vague, generic judgments. The problem is worst when no reference answer is available. This paper presents Eval-Instruct, a pipeline for building more informative training data for critique generation.
  3. CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language Models (2023 · 59 citations)
    General-purpose LLMs are mostly trained on short, task-oriented exchanges. As a result, they handle long social conversations poorly, especially when asked to stay in a specific persona. Prompting them to role-play tends to lose consistency and liveliness over many turns. Classic persona-based dialogue covers only…

All works

5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsXiao Liu, Xuanyu Lei, Shengyuan Wang, et al.arXiv:2311.18743 · 73 citations
  2. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model GenerationPei Ke, Bosi Wen, Zhuoer Feng, et al.arXiv:2311.18702 · 68 citations
  3. ToMBench: Benchmarking Theory of Mind in Large Language Models · original ↗ · no summary yet · Proceedings of the 62nd Annual Meeting of the Association for Computational…Zhuang Chen et al.2024 · 60 citations
  4. CharacterGLM: Customizing Chinese Conversational AI Characters with Large Language ModelsJinfeng Zhou, Zhuang Chen, Dazhen Wan, et al.arXiv:2311.16832 · 59 citations
  5. IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation · original ↗ · no summary yet · Proceedings of the 64th Annual Meeting of the Association for Computational…Bosi Wen et al.2026 · 1 citation

 Co-authors here

12 of 19 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 394 times (of the 141,840 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated

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