MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification (2025 · 19 citations)
The paper targets two gaps in multimodal math reasoning. There is no strong verifier for checking answers from multimodal LLMs, and there is little long chain-of-thought (CoT) training data with images. The authors build two 7B models. MM-Verifier is an outcome reward model that judges whether a solution to an…
Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making (2026 · 2 citations)
Medical LLMs score well on static benchmarks but often stall in real consultations: they rarely ask for missing facts, and they may hallucinate when filling gaps.
Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database Exploration (2026)
Most Text-to-SQL benchmarks test one-shot translation of a fixed question into a read-only query. Real database work is different: users refine goals over several turns and often need to change data, not just read it. The authors introduce DySQL-Bench to evaluate LLM agents in this setting. It contains 1,072…
Training Verifier to Assessing Complex Real-World Tool-Use Trajectories (2026)
LLM agents that handle multi-turn customer-service style tasks need training dialogues that reflect real user–agent collaboration.

All works

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

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning ↗arXiv:2503.19470 · no summary yetMingyang Chen et al.2025 · 99 citations
MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought VerificationAnnual Meeting of the Association for Computational Linguistics (ACL)Linzhuang Sun, Hao Liang, Jingxuan Wei, et al.2025 · 19 citations
Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-MakingarXiv:2602.06570Chengfeng Dou, Fan Yang, Fei Li, et al.2026 · 2 citations
Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database ExplorationFindings of the Association for Computational LinguisticsLinzhuang Sun, Tianyu Guo, Hao Liang, et al.2026
Training Verifier to Assessing Complex Real-World Tool-Use TrajectoriesFindings of the Association for Computational LinguisticsLinzhuang Sun, Mingyang Chen, Hao Liang, et al.2026

Co-authors here

12 of 18 co-authors with a page, the most papers together first.

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 151 times (of the 149,439 papers whose bibliographies we read); 42 citing papers with a page here →.

Updated 1 November 2026