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Dezhi Hong

Dezhi Hong has 2 papers in our library, in 2026, most of them on English, Language models & pretraining, Dialogue systems; often with Thomas Butler.

2 papers in our library · 2026

OpenAlex · h-index 2 · 6 works · 39 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #11950

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

🏢AmazonSeattle · United States2026 · 2 paperscurrent🏢MicrosoftRedmond · United States2026 · 1 papercurrent

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 · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.English · 2 worksDialogue systems · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. DialectLLM: A Dialect-Aware Dialog[ue] Generation Framework Beyond Standard American English (2026)
    Most English speakers worldwide do not use Standard American English (SAE). LLMs often misidentify other dialects and produce caricatured text for their speakers. Existing generators lean on eWAVE, which covers only grammar, and apply its features wholesale. The authors present DialectLLM, a pipeline that builds…
  2. English is Not All You Need: Systematically Exploring the Role of Multilinguality in LLM Post-Training (2026)
    Most LLM post-training is still done almost entirely in English. This paper asks whether that choice costs performance, in English and in other languages, and how the answer changes with model size and task type. The authors ran 220 supervised fine-tuning runs on Qwen-3 (0.6B, 1.7B, 8B) and Gemma-3 (1B, 4B). They…

 Co-authors here

1 co-author with a page, the most papers together first.

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