works on

From the 1 of 18 linked papers with an AI index.

collaborators

18 papers

cs.CL2026

Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction

Pan Wang, Yihao Hu, Hang Wang +6

Self-correction is particularly useful when a failure constrains the next repair. Coding agents benefit from this property because compilers, tests, and execution traces turn many…

cs.AI2026

SHE: Trajectory-driven Safety Harness Evolution for LLM Agents

Wanying Qu, Qinghua Mao, Yu Li +12

The safety of large language model (LLM) agents depends not only on model weights but also on the agent harness that manages context, memory, tools, permissions, and runtime contro…

cs.RO2026

ReTouch: Empowering Contact-Rich Dexterous Manipulation with Online-Refined Tactile Prediction

Shiqi Zhang, Xin Zhang, Yedong Shen +9

Fusing tactile signals has proven effective for contact-rich manipulation, enabling robots to perceive contact states and adapt to rapidly changing physical interactions. Yet effec…

cs.RO2026

TacWAM: Anchor-Guided World Action Model with Mechanics-Aware Tactile Prediction

Lei Jin, Yiding Ma, Xin Zhang +3

The paper introduces TacWAM, a mechanics-aware tactile world action model that predicts future tactile signals and uses them as supervision for training contact-rich robot manipula…

cs.RO2026

WorldScape Policy 2.0: Empowering Steerable World Action Modeling with Reasoning-Augmented Memory

Haisheng Su, Zongdai Liu, Xin Jin +13

World Action Models (WAMs) offer a promising paradigm for robotic manipulation by jointly modeling visual state transitions and robot actions. However, existing WAMs are constraine…

cs.RO2026

Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control

Jianjie Fang, Yongyan Xu, Ziyou Wang +13

World models are rapidly becoming a core infrastructure for embodied intelligence and interactive agents: they provide controllable simulators in which agents can perceive, act, fo…