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Yujia Wang

Yujia Wang has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning, Bias, fairness & safety; often with Jingbo Shang, Yongqi Tong, Dawei Li.

2 papers in our library · 2023–2024

OpenAlex · ORCID · Wikidata · h-index 12 · 60 works · 503 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 130 times in our library · ⭐ Paper Stars ranking: #5758

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. 11 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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation (2023 · 136 citations)
    Most toxicity detectors are trained on social media text. Users of LLM chatbots behave differently: they phrase harmful intent as questions or instructions, and they sometimes use "jailbreaking" prompts that look benign but aim to make the model bypass its policies. To study this gap, the authors built ToxicChat, the…
  2. Can LLMs Learn from Previous Mistakes? Investigating LLMs' Errors to Boost for Reasoning (2024 · 57 citations)
    The paper asks whether large language models can improve their reasoning by learning from their own errors, rather than only imitating gold-standard Chain-of-Thought (CoT) rationales.

 Co-authors here

7 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 130 times (of the 149,439 papers whose bibliographies we read); 35 citing papers with a page here →.

Updated

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