collaborators

8 papers

cs.RO2026

ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts

Mingxin Wang, Bin Hu, Bin Qian +12

World Action Models (WAMs) have emerged as a promising paradigm by jointly modeling robot actions and future visual dynamics. However, their reliance on pixel-generative future sup…

q-bio.OT2026

Orientation Reading by Production Vision-Language Models on Optotype Charts: A Controlled Multi-Model Evaluation Across Reasoning Modes, Prompts, and Access Modalities

Shahryar Wasif, Avneek Sandhu, Bin Hu

OBJECTIVES: Vision-language models are increasingly used to interpret medical and everyday images through consumer chat interfaces, yet their ability to read orientation - the sing…

cs.CV2026

ABot-M0.5: Unified Mobility-and-Manipulation World Action Model

Ronghan Chen, Yandan Yang, Zuojin Tang +18

Mobile manipulation is a key capability for general-purpose robots, yet remains challenging for current embodied learning methods. VLA policies are typically reactive and lack expl…

cs.CV2026

PhysEditWorld: A Large-Scale Dataset Toward Physics-Editable World Models

Bin Hu, Yanwen Ma, Jiehui Huang +14

Recent game world models can synthesize visually plausible, action-conditioned rollouts. However, their interaction behaviors often remain limited to exploratory or wandering traje…

q-bio.OT2026

PROMPT: A Pre-registered Randomized Protocol for Component-Level Evaluation of Clinical AI Prompts

Bin Hu, Avneek Sandhu, Shahryar Wasif

BACKGROUND:Prompt engineering shapes medical AI outcomes, but prompt components are rarely tested as clinical interventions. We developed PROMPT (Pre-registered Randomized Outcome…

q-bio.NC2026

Dynamic Computerized Tumbling-E Testing for Temporal Reliability of Human Sequential Perceptual Decisions

Avneek Sandhu, Bin Hu

OBJECTIVES: Visual acuity and tumbling-E tasks are often treated as static threshold measures, yet sequential perceptual decisions unfold over time. A computerized tumbling-E task…