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20242026
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7 papers · 1 filter

astro-ph.IM2026

The science case for an in-situ measurement platform in the Venus clouds

Maureen Cohen, Joanna Egan, Martin Airey +14

The next step for Venus exploration after the remote sensing missions of the early 2030s will be in-situ aerial platforms, the Venus equivalent of rovers for Mars. Sophisticated Ve…

cs.CV2026

SituHOI: Scalable Capture of Scene-Situated Full-Body Human-Object Interaction

Qifan Wang, Qihang Fang, Boao Shi +4

Modeling human-object interaction (HOI) in real environments requires jointly representing whole-body motion, manipulated objects, and scene geometry, yet existing datasets trade o…

cs.RO2026

The Imitator Game: Benchmarking Robot Imitative Ability Beyond Action Prediction

Xunzhe Zhou, Yiyang Cai, Fengyi Wang +9

Humans imitate at the level of intent: given a demonstration, we infer its goal and carry it out with whatever tools, objects, and layouts are at hand. Current robot policies inste…

cs.RO2026

Geometric Entropy: When Trajectory Diversity Helps and Hurts in Imitation Learning

Qian Luo, Ruizhe Liu, Pei Zhou +2

We study how trajectory-shape diversity in demonstrations affects imitation learning (IL) performance across models, tasks, and data scales. We introduce Geometric Entropy (H_G), a…

cs.RO2026

DISC: Decoupling Instruction from State-Conditioned Control via Policy Generation

Hanxiang Ren, Pei Zhou, Xunzhe Zhou +1

Language-conditioned manipulation policies typically process instructions and observations through shared network parameters. This task-state entanglement provides a pathway for ob…

cs.LG2026

Reinforcing Human Behavior Simulation via Verbal Feedback

Weiwei Sun, Xuhui Zhou, Jiarui Liu +13

Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying "that was rude" or a friend explaining "here's why that hurt"). Yet, learning from feedback for…

cs.RO2026

DexHoldem: An Agentic Robotics Benchmark for Dexterous Manipulation in Texas Hold'em

Feng Chen, Tianzhe Chu, Li Sun +6

Evaluating embodied systems with real dexterous hardware requires more than isolated motor-skill tests: an agent must perceive a changing scene (e.g. a tabletop), choose a context-…