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Zhaoyang Xu

2 accepted papers

2026

Breaking the Regional Perception Bottleneck of Multimodal Large Language Models via External Reasoning Framework

CVPR 2026

High-quality pixel-level responses remain a major bottleneck for multimodal large language models (MLLMs) in regional perception. Existing approaches generally attach regression decoders to MLLM features, achieving strong grounding performance but compromising end-to-end design and increasing traini

Cited by 0SourceScholar
2025

MMAU: A Holistic Benchmark of Agent Capabilities Across Diverse Domains

NAACL 2025findings

Recent advances in large language models (LLMs) have increased the demand for comprehensive benchmarks to evaluate their capabilities as human-like agents. Existing benchmarks, while useful, often focus on specific application scenarios, emphasizing task completion but failing to dissect the underly…