← Search

Yuancheng Wei

4 accepted papers

2026

EduDiag: A Benchmark for Educational Diagnostic Reasoning with Error Tracing and Correction on Large Multimodal Models

CVPR 2026

Large multimodal models (LMMs) have achieved impressive performance on multimodal reasoning, becoming crucial technology for the advancement of intelligent question-answering systems. In real-world educational scenarios, effective teaching extends far beyond providing answers. Experienced teachers a

Cited by 0SourceScholar
2026

OmniDenseCap: Scripting Multi-Scene Videos with Time-Aware and Structural Audio-Visual Captions

ICML 2026poster

This paper proposes Omni Dense Captioning, a novel task designed to generate continuous, fine-grained, and structured audio-visual narratives with explicit timestamps. To ensure dense semantic coverage, we introduce a six-dimensional structural schema to create "script-like" captions, enabling reade…

Cited by 0SourceScholar
2025

CADReview: Automatically Reviewing CAD Programs with Error Detection and Correction

ACL 2025long

Computer-aided design (CAD) is crucial in prototyping 3D objects through geometric instructions (i.e., CAD programs). In practical design workflows, designers often engage in time-consuming reviews and refinements of these prototypes by comparing them with reference images. To bridge this gap, we in…

Cited by 0SourcePDFScholar
2025

VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models

CVPR 2025highlight

Vision-language generative reward models (VL-GenRMs) play a crucial role in aligning and evaluating multimodal AI systems, yet their own evaluation remains under-explored. Current assessment methods primarily rely on AI-annotated preference labels from traditional VL tasks, which can introduce biase…