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Yiming Luo

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Preprint Oct 2026

FOMI: A Force-Feedback Manipulation Interface for Teaching Contact-Rich Manipulation

Robot-free collection with handheld interfaces enables scalable acquisition of human demonstrations for policy learning. However, existing handheld interfaces often provide limited intuitive force feedback, making contact-rich demonstration collection challenging for human operators. To address this, we present FOMI, a...

Yi-Shu Shen, Yi-Ming Luo, Rui-Lin Wang et al. · 0 citations
Preprint Aug 2026

Mind the Context: Continual Learning of Socially Appropriate Robot Actions via Environmental-Social Disentanglement

Social robots are expected to operate across diverse environments, where similar arrangements can imply different socially appropriate actions, e.g., starting a conversation may be acceptable in a crowded home but disruptive in an office meeting. Because such norms and environments cannot all be anticipated in advance,...

Rafał Karpiński, Fethiye Irmak Doğan, Nikhil Churamani et al. · 0 citations
Preprint Aug 2026

Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization

This work presents Zero-WAM, a causal video-action model that executes unseen tasks by following in-context human video guidance, and proposes an automatic pipeline that converts task-sampled robot trajectories into semantically matched human videos, yielding HumanGen, a dataset of 74.2K human-robot ICL pairs across 8....

Jia-Min Zhou, Qihang Zhang, Gangwei Xu et al. · 15 citations
Preprint Aug 2026

ELBench: A Multi-Dimensional Benchmark for Education-Facing Large Language Models

ELBench is introduced, the first benchmark to evaluate all four requirements (General Capability, Safety and Trustworthiness, Basic Education, and High-Level Cultivation) on the same models under a common protocol, combining curated public sources with newly synthesized safety and cultivation data.

Yi-Lin Jiang, Xiao-Rong Zhu, Fei Tan et al. · 0 citations
Jul 2026

Native Video-Action Pretraining for Generalizable Robot Control

LingBot-VA 2.0 is presented, a video-action foundation model built from the ground up for embodiment, which introduces a semantic visual-action tokenizer, which aligns visual representations with both semantics and actions, improving instruction following and action precision in subsequent policy learning.

Qihang Zhang, Lin Li, Luyao Zhang et al. · 11 citations · ⚡3
Preprint Aug 2026

ADE: Agentic Data Evolution Framework for Human-Centered Objectives

Agentic Data Evolution is proposed, a data-centric framework that organizes synthetic supervision as evolving data snapshots through a closed-loop Observation-Variation-Selection procedure, where a steady-state admission mechanism acts as a quality ratchet that conservatively gates updates for sustained cross-round imp...

Yang Yu, Yi-Lin Jiang, Zexuan Fei et al. · 0 citations

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