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cs.AI2026
Senses Wide Shut: A Representation-Action Gap in Omnimodal LLMs
Trung Nguyen Quang, Yiming Gao, Fanyi Pu +3
When an omnimodal large language model accepts a question whose textual premise contradicts what it actually sees or hears, does the failure lie in perception or in action? Recent…
cs.AI2026
RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark
Yang Shi, Yuhao Dong, Yue Ding +22
The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question rem…
cs.AI2026
VTC-Bench: Evaluating Agentic Multimodal Models via Compositional Visual Tool Chaining
Xuanyu Zhu, Yuhao Dong, Rundong Wang +9
Recent advancements extend Multimodal Large Language Models (MLLMs) beyond standard visual question answering to utilizing external tools for advanced visual tasks. Despite this pr…