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Jinfeng Bai

Jinfeng Bai has 3 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning, Bias, fairness & safety; often with Hao Sun, Jie Tang, Ming Ding.

3 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 24 · 78 works · 1,938 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 110 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #7795

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. 5 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. Unveiling the Implicit Toxicity in Large Language Models (2023 · 72 citations)
    Most red-teaming work on large language models looks for overtly abusive outputs, which standard toxicity detectors catch easily.
  2. GPT Can Solve Mathematical Problems Without a Calculator (2023 · 41 citations)
    A common belief holds that LLMs cannot reliably do arithmetic without calling an external calculator, especially multiplying numbers longer than 8 digits or working with decimals and fractions.
  3. MuMath-Code: Combining Tool-Use Large Language Models with Multi-perspective Data Augmentation for Mathematical Reasoning (2024 · 17 citations)
    Open-source LLMs lag behind proprietary systems in mathematical reasoning. Prior work tackled this in one of two ways: generating large amounts of extra training data, or teaching models to call a Python interpreter. MuMath-Code combines both. The authors take questions created with the multi-perspective augmentation…

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation ↗IEEE/CVF International Conference on Computer Vision (ICCV) · no summary yetYuxiang Wei et al.2023 · 263 citations
  2. GPT Can Solve Mathematical Problems Without a CalculatorarXiv:2309.03241Zhen Yang, Ming Ding, Qingsong Lv, et al.2023 · 41 citations

 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.

 Cited by

Papers of our library cite their works 110 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

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