5 citations · 6 across the 11 of their papers we have counts for
3 papers · 1 filter
QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs
Santiago Gonzalez, Alireza Amiri Bavandpour, Peter Ye +48
As Large Language Models (LLMs) saturate elementary benchmarks, the research frontier has shifted from generation to the reliability of automated evaluation. We demonstrate that st…
Milestones over Outcome: Unlocking Geometric Reasoning with Sub-Goal Verifiable Reward
Jianlong Chen, Daocheng Fu, Shengze Xu +6
Multimodal Large Language Models (MLLMs) struggle with complex geometric reasoning, largely because "black box" outcome-based supervision fails to distinguish between lucky guesses…
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering
Jiaxin Lu, Zetian Jiang, Tianzhe Wang +1
Existing graph matching methods typically assume that there are similar structures between graphs and they are matchable. However, these assumptions do not align with real-world ap…