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Jitao Sang

Jitao Sang has 3 papers in our library, in 2023–2026, most of them on Language models & pretraining, Bias, fairness & safety; often with Chao Peng, Guohai Xu, Haotian Xu.

3 papers in our library · 2023–2026

OpenAlex · ORCID · Wikidata · h-index 27 · 171 works · 2,327 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 124 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #7241

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. 2 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. CValues: Measuring the Values of Chinese Large Language Models from Safety to Responsibility (2023 · 64 citations)
    Existing Chinese LLM benchmarks such as C-EVAL, M3KE and GAOKAO-Bench mostly test knowledge and reasoning.
  2. Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks (2026 · 10 citations)
    LLM agents on long tasks such as deep research or multi-step tool use accumulate large interaction histories.
  3. CSPO: Alleviating Reward Ambiguity for Structured Table-to-LaTeX Generation (2026 · 1 citation)
    Turning images of tables into LaTeX code is useful for digitizing scientific documents. However, multimodal LLMs often get cell merges, line styles or cell values wrong, or produce code that does not compile. The authors argue that standard RL post-training (e.g., GRPO) scores the whole output with one reward. This…

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. AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation ↗arXiv:2311.07397 · no summary yetJunyang Wang et al.2023 · 67 citations
  2. CValues: Measuring the Values of Chinese Large Language Models from Safety to ResponsibilityarXiv:2307.09705Guohai Xu, Jiayi Liu, Ming Yan, et al.2023 · 64 citations

 Co-authors here

9 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 124 times (of the 149,439 papers whose bibliographies we read); 35 citing papers with a page here →.

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