---
title: "Yung-Sung Chuang — author profile and papers"
description: "Yung-Sung Chuang, OpenAI (United States): 2 papers on Elamur Research (2022–2023), h-index 18 — affiliations, topics, co-authors and who cites them in…"
canonical: "https://research.elamur.ai/free/en/authors/yung-sung-chuang/"
---
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[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yung-Sung Chuang

# Yung-Sung Chuang

2 papers on this site · 2022–2023

current affiliation [OpenAI (United States)](https://md.research.elamur.ai/free/en/companies/openai/), San Francisco, United States; [Massachusetts Institute of Technology](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/), Cambridge, United States

Yung-Sung Chuang has 2 papers on this site, in 2022–2023, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Hongyin Luo](https://md.research.elamur.ai/free/en/authors/hongyin-luo/), [James Glass](https://md.research.elamur.ai/free/en/authors/james-glass/), [Yoon Kim](https://md.research.elamur.ai/free/en/authors/yoon-kim/).

[OpenAlex](https://openalex.org/A5058729228) · [ORCID](https://orcid.org/0000-0002-1723-5063) · [**h-index 18**](https://openalex.org/authors/A5058729228) · [48 works](https://openalex.org/works?filter=author.id:A5058729228) · [1 579 citations](https://openalex.org/works?filter=author.id:A5058729228&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[2 works on this site](https://md.research.elamur.ai/free/en/authors/yung-sung-chuang/#papers) · [496 citations in our library](https://md.research.elamur.ai/free/en/authors/yung-sung-chuang/cited-by/) · 4 more works in our library

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yung-Sung+Chuang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yung-Sung+Chuang) · [dblp](https://dblp.org/search?q=Yung-Sung+Chuang) · [ACL Anthology](https://aclanthology.org/search/?q=Yung-Sung+Chuang)

## Affiliations

- [Massachusetts Institute of Technology](https://md.research.elamur.ai/free/en/universities/massachusetts-institute-of-technology/) · Cambridge, United States —current · 2020–2025 on 26 papers
- [OpenAI (United States)](https://md.research.elamur.ai/free/en/companies/openai/) · San Francisco, United States —current · 2025 on 1 paper
- [National Taiwan University](https://md.research.elamur.ai/free/en/universities/national-taiwan-university/) · Taipei, Taiwan —2019–2024 on 16 papers
- [MIT Computer Science and Artificial Intelligence Laboratory](https://md.research.elamur.ai/free/en/labs/mit-computer-science-and-artificial-intelligence-laboratory/) · Cambridge, United States —2020–2024 on 9 papers
- [IBM (United States)](https://md.research.elamur.ai/free/en/companies/ibm/) · Armonk, United States —2022–2024 on 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

## Topics

[Language models & pretraining 1](https://md.research.elamur.ai/free/en/topics/language-models/)

## Works by year

### 2020s

[**2023** 1 paper](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/papers/chuang-2022-diffcse-difference-based-contrastive-learning/)

## Papers

The most cited first (OpenAlex and our library).

1. **[DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/chuang-2022-diffcse-difference-based-contrastive-learning/)** *(2022 · 269 citations)* Unsupervised sentence embedding methods such as SimCSE train an encoder so that two dropout-perturbed copies of a sentence stay close together.
2. **[DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/)** *(2023 · 261 citations)* Large language models often produce statements that conflict with facts they saw during pretraining, which limits their use in high-stakes domains.

## Also in our library

4 more works of theirs are in our library without a page here yet; they will appear as we publish them.

## Co-authors here

7 co-authors with a page, the most papers together first.

- [Hongyin Luo](https://md.research.elamur.ai/free/en/authors/hongyin-luo/) ×2
- [James Glass](https://md.research.elamur.ai/free/en/authors/james-glass/) ×2
- [Yoon Kim](https://md.research.elamur.ai/free/en/authors/yoon-kim/) ×2
- [Pengcheng He](https://md.research.elamur.ai/free/en/authors/pengcheng-he/)
- [Scott Yih](https://md.research.elamur.ai/free/en/authors/scott-yih/)
- [Yang Zhang](https://md.research.elamur.ai/free/en/authors/yang-zhang/)
- [Yujia Xie](https://md.research.elamur.ai/free/en/authors/yujia-xie/)

## Cited by

Papers of our library cite their works 496 times (of the 140 884 papers whose bibliographies we read); [21 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yung-sung-chuang/cited-by/).
