Elamur Research⌕
☰
home / authors / Kaiwen Luo

Kaiwen Luo

Kaiwen Luo has 2 papers in our library, in 2026, most of them on Speech & spoken language, Language models & pretraining, Evaluation & benchmarks; often with Jin Wang, Kun Wang, Li Sun.

2 papers in our library · 2026

OpenAlex · h-index 1 · 11 works · 1 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #13699

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

🎓Nanyang Technological UniversitySingapore · Singapore2026 · 3 paperscurrent🎓North China Electric Power UniversityBeijing · China2026 · 2 paperscurrent

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.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksSignal Processing · 1 work

🧭 Topics 3Research subjects and languages the work is about.Speech & spoken language · 2 worksEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. HearSay Benchmark: Do Audio LLMs Leak What They Hear? (2026)
    Audio Large Language Models (ALLMs) are trained on huge amounts of speech. The authors ask whether this training lets them work out private facts about a speaker from the voice alone, with no help from what is actually said. To test this, they built HearSay, a benchmark of more than 22,000 real recordings. Most clips…
  2. RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios (2026)
    Audio Large Models (ALLMs) score well on clean benchmarks, but their behavior in realistic noisy settings has rarely been measured.

 Co-authors here

10 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.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/kaiwen-luo/