works on

From the 2 of 9 linked papers with an AI index.

activity
20242026
collaborators

9 papers

cs.AI2026

RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination

Haotian Liang, Mingkang Chen, Yufei Huang +27

The paper introduces RxBrain, a foundation model that jointly reasons over language and visual inputs to create embodied plans, using a multimodal Mixture-of-Transformers architect…

cs.RO2026

ProAct: A Benchmark and Multimodal Framework for Structure-Aware Proactive Response

Xiaomeng Zhu, Fengming Zhu, Weijie Zhou +8

The paper introduces ProAct-75, a benchmark of 75 proactive tasks with step‑level annotations and task graphs, and presents ProAct-Helper, a multimodal LLM that uses these graphs f…

cs.RO2026

UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations

Tingyu Yuan, Biaoliang Guan, Wen Ye +8

In embodied intelligence, the embodiment gap between robotic and human hands brings significant challenges for learning from human demonstrations. Although some studies have attemp…

cs.CV2026

Listening with the Eyes: Benchmarking Egocentric Co-Speech Grounding across Space and Time

Weijie Zhou, Xuantang Xiong, Zhenlin Hu +6

In situated collaboration, speakers often use intentionally underspecified deictic commands (e.g., ``pass me \textit{that}''), whose referent becomes identifiable only by aligning…

cs.IR2026

SteerEval: A Framework for Evaluating Steerability with Natural Language Profiles for Recommendation

Joyce Zhou, Weijie Zhou, Doug Turnbull +1

Natural-language user profiles have recently attracted attention not only for improved interpretability, but also for their potential to make recommender systems more steerable. By…

cs.CV2025

PhysVLM-AVR: Active Visual Reasoning for Multimodal Large Language Models in Physical Environments

Weijie Zhou, Xuantang Xiong, Yi Peng +5

Visual reasoning in multimodal large language models (MLLMs) has primarily been studied in static, fully observable settings, limiting their effectiveness in real-world environment…