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Tianshi Zheng

Tianshi Zheng has 3 papers in our library, in 2026, most of them on Language models & pretraining, Reasoning, Knowledge graphs & ontologies; often with Baixuan Xu, Yangqiu Song, Chunkit Chan.

3 papers in our library · 2026

OpenAlex · h-index 3 · 40 works · 46 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 33 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #11501

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

🎓Hong Kong University of Science and TechnologyHong Kong · China2023–2026 · 49 paperscurrent🎓University of Hong KongPok Fu Lam · 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Knowledge graphs & ontologies · 1 workLanguage models & pretraining · 1 workReasoning · 1 workVision & language · 1 work

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction (2026 · 4 citations)
    Graph-based RAG systems usually build their knowledge graph once, judge it by intrinsic criteria such as precision or coverage, and then use it unchanged for question answering.
  2. DIXITWORLD: Evaluating Multimodal Abductive Reasoning in Vision-Language Models with Multi-Agent Dixit Gameplay (2026 · 2 citations)
    The paper asks how well vision-language models (VLMs) handle multimodal abductive reasoning, meaning proposing and choosing the most plausible explanation from incomplete visual evidence.
  3. InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge Profiling (2026 · 1 citation)
    Choosing which large language model should answer a given query becomes difficult as the number of specialized models grows.

All works

6 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. From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery ↗arXiv:2505.13259 · no summary yetTianshi Zheng et al.2025 · 39 citations
  2. AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph ConstructionAnnual Meeting of the Association for Computational Linguistics (ACL)Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, et al.2026 · 4 citations
  3. Legal Rule Induction: Towards Generalizable Principle Discovery from Analogous Judicial Precedents ↗arXiv:2505.14104 · no summary yetWei Fan et al.2025 · 3 citations
  4. DIXITWORLD: Evaluating Multimodal Abductive Reasoning in Vision-Language Models with Multi-Agent Dixit GameplayAnnual Meeting of the Association for Computational Linguistics (ACL)Yunxiang MO, Tianshi Zheng, Qing Zong, et al.2026 · 2 citations
  5. InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge ProfilingAnnual Meeting of the Association for Computational Linguistics (ACL)Haochen Shi, Tianshi Zheng, Weiqi Wang, et al.2026 · 1 citation
  6. Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning ↗arXiv:2605.25920 · no summary yetWei Fan et al.2026 · 1 citation

 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 33 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

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