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Yiming Chen

Yiming Chen has 3 papers in our library, in 2026, most of them on Language models & pretraining, Speech & spoken language, Code & programming languages; often with Robby T. Tan, Chen Zhang, Haizhou Li.

3 papers in our library · 2026

OpenAlex · ORCID · h-index 5 · 19 works · 162 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 71 times in our library · ⭐ Paper Stars ranking: #6972

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

🎓National University of SingaporeSingapore · Singapore2026 · 1 papercurrent🎓Harbin Engineering UniversityHarbin · China2016–2025 · 6 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 8 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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksSignal Processing · 1 workInformation Systems · 2 worksSoftware · 2 works

🧭 Topics 3Research subjects and languages the work is about.Speech & spoken language · 1 workCode & programming languages · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. VoiceBench: Benchmarking LLM-Based Voice Assistants (2026 · 74 citations)
    Voice assistants built on audio-capable LLMs, such as GPT-4o-style systems, have had no common yardstick. Earlier work mostly reported ASR scores, anecdotal examples, or small spoken QA sets made from clean TTS audio. The authors address this with VoiceBench, an evaluation suite of 6,783 spoken instructions in eight…
  2. CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks (2026 · 13 citations)
    LLMs increasingly act as evaluators that compare, rank, or score code, yet little is known about how reliable they are in this role.
  3. TreeDiff: AST-Guided Code Generation with Diffusion LLMs (2026 · 3 citations)
    Diffusion-based language models (DLLMs) generate text by iteratively un-masking a corrupted sequence. They do this poorly for code, partly because training masks tokens uniformly at random, ignoring program grammar. As a result, models often produce syntactically broken drafts and miss long-range relations such as…

 Co-authors here

5 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 71 times (of the 149,439 papers whose bibliographies we read); 21 citing papers with a page here →.

Updated

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