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…
GenProve: Learning to Generate Text with Fine-Grained Provenance (2026)
Citations in LLM answers often point only to whole documents. They do not show which sentence backs a claim or how that sentence is used, so checking the answer stays hard. The authors define a task called Generation-time Fine-grained Provenance. The model writes an answer and, for each sentence, emits structured…
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.

Co-authors here

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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 15 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated 1 November 2026