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Tong Xu

Tong Xu has 4 papers in our library, in 2023–2026, most of them on Language models & pretraining, Information extraction, Evaluation & benchmarks; often with Enhong Chen, Chao Zhang, Chaoyou Fu.

4 papers in our library · 2023–2026

OpenAlex · h-index 1 · 8 works · 1 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 313 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #1879

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

🎓University of Science and Technology of ChinaHefei · China2026 · 6 paperscurrent🎓Zhejiang UniversityHangzhou · China2026 · 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 1 workComputational Theory and Mathematics · 1 work

🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 3 worksVision & language · 1 workInformation extraction · 1 workEvaluation & benchmarks · 1 workReasoning · 1 work

💡 Concepts 2Key ideas and methods explained on our concept pages.Large language models · 1 workInformation extraction · 1 work

 Works by year

2020s

20262 papers20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. A Survey on Multimodal Large Language Models (2023 · 1,069 citations)
    Yin and colleagues give one of the earliest overviews of Multimodal Large Language Models (MLLMs). These are systems that use a pre-trained LLM as the reasoning core and attach perception for images, video, audio and other signals. The authors argue that LLMs reason well but cannot see, and large vision models…
  2. Large Language Models for Generative Information Extraction: A Survey (2023 · 406 citations)
    Information extraction (IE) turns raw text into structured knowledge such as entities, relations and events.
  3. Mock Worlds, Real Skills: Building Small Agentic Language Models with Synthetic Tasks, Simulated Environments, and Rubric-Based Rewards (2026 · 1 citation)
    Small language models usually lag well behind large, expensive LLMs on agentic tool-use tasks. Reinforcement learning could help, but two obstacles hold it back. Public agentic datasets are narrow and often too easy, so RL rollouts give little learning signal. Real APIs are also costly, unstable and limited in scope.…
  4. PRIME: A Process-Outcome Alignment Benchmark for Verifiable Reasoning in Mathematics and Engineering (2026)
    RLVR (reinforcement learning with verifiable rewards) relies on verifiers that usually check only whether a model's final answer matches the reference.

All works

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

  1. A Survey on Multimodal Large Language ModelsarXiv:2306.13549Shukang Yin, Chaoyou Fu, Sirui Zhao, et al.2023 · 1,069 citations
  2. Large Language Models for Generative Information Extraction: A SurveyFrontiers of Computer ScienceDerong Xu, Wei Chen, Wenjun Peng, et al.2023 · 406 citations
  3. Mock Worlds, Real Skills: Building Small Agentic Language Models with Synthetic Tasks, Simulated Environments, and Rubric-Based RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanjie Lyu, Chengyu Wang, Lei Shen, et al.2026 · 1 citation
  4. PRIME: A Process-Outcome Alignment Benchmark for Verifiable Reasoning in Mathematics and EngineeringAnnual Meeting of the Association for Computational Linguistics (ACL)Xiangfeng Wang, Hangyu Guo, Yanlin Lai, et al.2026
  5. To Paraphrase or Not: Efficient Comment Detoxification with Unsupervised Detoxifiability Discrimination ↗Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yetJing Ke et al.2026
  6. Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetDerong Xu et al.2026
  7. MolSafeEval: A Benchmark for Uncovering Safety Risks in AI-Generated Molecules ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetTong Xu et al.2026

 Co-authors here

12 of 19 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 313 times (of the 149,439 papers whose bibliographies we read); 63 citing papers with a page here →.

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