3 papers
cs.CV2026
Ego-Grounding for Personalized Question-Answering in Egocentric Videos
Junbin Xiao, Shenglang Zhang, Pengxiang Zhu +1
We present the first systematic analysis of multimodal large language models (MLLMs) in personalized question-answering requiring ego-grounding - the ability to understand the came…
cs.AI2026
MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome
Fangda Ye, Yuxin Hu, Pengxiang Zhu +19
Recent progress in deep research systems has been impressive, but evaluation still lags behind real user needs. Existing benchmarks predominantly assess final reports using fixed r…
cs.AI2026
MiroFlow: Towards High-Performance and Robust Open-Source Agent Framework for General Deep Research Tasks
Shiqian Su, Sen Xing, Xuan Dong +13
Despite the remarkable progress of large language models (LLMs), the capabilities of standalone LLMs have begun to plateau when tackling real-world, complex tasks that require inte…