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Steffi Chern

Steffi Chern has 2 papers in our library, in 2023–2024; often with Pengfei Liu, Chunting Zhou, Ethan Chern.

2 papers in our library · 2023–2024

OpenAlex · h-index 4 · 18 works · 90 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 414 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5989

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

🎓Carnegie Mellon UniversityPittsburgh · United States2023–2026 · 9 paperscurrent🎓University of PennsylvaniaPhiladelphia · United States2026 · 1 papercurrent

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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksSocial Sciences · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksSociology and Political Science · 2 worksComputer Vision and Pattern Recognition · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios (2023 · 160 citations)
    Large language models such as ChatGPT write fluent long-form answers that may contain factual errors. Classic fact-checking setups rarely fit this case. They usually assume that the claim to check, or the evidence for it, is already given. LLM outputs instead come without either, and they are long, with no clear unit…
  2. Halu-J: Critique-Based Hallucination Judge (2024 · 8 citations)
    LLMs often produce factually wrong statements. Retrieval-based detectors usually reduce the check to a bare label. They give little justification, can be thrown off by off-topic retrieved passages, and weigh all evidence equally. Halu-J addresses this with an open judge model of 7 billion parameters. Given a claim…

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain ScenariosarXiv:2307.13528I-Chun Chern, Steffi Chern, Shiqi Chen, et al.2023 · 160 citations
  2. OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI ↗arXiv:2406.12753 · no summary yetZhen Huang et al.2024 · 56 citations
  3. Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate ↗arXiv (Cornell University) · no summary yetSteffi Chern et al.2024 · 17 citations
  4. Halu-J: Critique-Based Hallucination JudgearXiv:2407.12943Binjie Wang, Steffi Chern, Ethan Chern, et al.2024 · 8 citations

 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 414 times (of the 149,439 papers whose bibliographies we read); 118 citing papers with a page here →.

Updated

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