3 papers
cs.AI2026
GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines
Yumeng Fu, Jiayin Zhu, Lingling Zhang +5
Geometry problem solving (GPS) poses significant challenges for Multimodal Large Language Models (MLLMs) in diagram comprehension, knowledge application, long-step reasoning, and a…
cs.CL2026
GeoChallenge: A Multi-Answer Multiple-Choice Benchmark for Geometric Reasoning with Diagrams
Yushun Zhang, Weiping Fu, Zesheng Yang +6
Evaluating the symbolic reasoning of large language models (LLMs) calls for geometry benchmarks that require multi-step proofs grounded in both text and diagrams. However, existing…
cs.AI2026
ErrEval: Error-Aware Evaluation for Question Generation through Explicit Diagnostics
Weiping Fu, Bifan Wei, Jingyi Hao +7
Automatic Question Generation (QG) often produces outputs with critical defects, such as factual hallucinations and answer mismatches. However, existing evaluation methods, includi…