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Chuang Wang

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Preprint Oct 2026

ReSight: Task-Driven Self-Improving Memory for Embodied Agents

Robots can use historical observations to answer spatiotemporal queries in familiar environments, but the presence of relevant evidence does not imply that existing tools support the operations a task requires. We introduce ReSight, a task-driven self-improving memory system for embodied agents that expands the capabil...

Li-Rong Che, Yang Chen, Yi-Meng Su et al. · 2 citations · ⚡1
#natural language process... Preprint Oct 2026

AdaRSI: On-Demand Recursive Self-Improvement for Embodied Agents

Pretrained vision-language-action models (VLAs) often fail midway through unseen long-horizon tasks. Recursive self-improvement (RSI) offers a remedy, but embodied RSI methods either refine the harness around a frozen executor and so cannot add a missing motion, or train the executor on persistent failures without aski...

Pei-Dong Wang, Ying Chang, Zhi-Ming Ma et al. · 4 citations
#machine learning Preprint Oct 2026

Harnessing VLM in Embodied RL: From Reward Regressor to Success Detector via Exploration-Augmented Key-Observation Gating

The proposed exploration-augmented key-observation gating first determines whether the current RL episode is judgment-worthy based on its similarity to a generated success trajectory, and proposes VLM success reward via Exploration-Augmented Key-Observation Gating (VLMeg) to well harness VLM for embodied reward design.

Xin Liu, Yu-Tong Jiang, Jia-Yue Su et al. · 0 citations
#artificial intelligence Preprint May 2026

DemoEvolve: Demonstration-Guided Harness Evolution under Sparse Feedback

Harness evolution enables frozen language model agents to adapt to unfamiliar tasks by modifying the external programs that govern their behavior. For long-horizon tasks, each rollout is costly, and a limited interaction budget may yield few examples of effective behavior. Sparse, delayed feedback also makes it difficu...

Li-Rong Che, Yu-Zhe Yang, Pei Lin et al. · 5 citations · ⚡1
Sep 2026

HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness

This work introduces HarnessVLN, a zero-shot, training-free framework that unifies instruction-following and object-goal navigation through a shared Agent Harness and demonstrates its applicability to both navigation tasks in real-world environments.

Yang Chen, Li-Rong Che, Zhen-Yu Huang et al. · 8 citations · ⚡2
Preprint Aug 2026

CoCoBench: A Cooperative Coordination Benchmark for Embodied Multi-Agent Task Planning

CoBench is introduced, a construct-level benchmark for evaluating multi-agent embodied coordination in executable household tasks and shows that coordination ability is highly construct-specific: strong overall performance does not imply balanced competence across different coordination types.

Yang Chen, Ye-Xin Xie, Li-Rong Che et al. · 0 citations

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