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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.RO2026

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation

Shaopeng Zhai, Qi Zhang, Tianyi Zhang +5

The paper introduces HELP, a pipeline that uses two specialized human operators to supervise a fleet of robots during post‑training of Vision‑Language‑Action models, improving huma…

cs.AI2026

-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows

Haoran Zhang, Luxin Xu, Zhilin Wang +11

The rise of personal assistant agents, e.g., OpenClaw, highlights the growing potential of large language models to support users across everyday life and work. A core challenge in…

cs.RO2026

Preserving Foundational Capabilities in Flow-Matching VLAs through Conservative SFT

Tianyi Zhang, Shaopeng Zhai, Haoran Zhang +2

Unconstrained fine-tuning of flow-matching Vision-Language-Action (VLA) models drives dense parameter overwrites, degrading pre-trained capabilities. We present Conservative Superv…

cs.RO2026

BlockVLA: Accelerating Autoregressive VLA via Block Diffusion Finetuning

Ruiheng Wang, Shuanghao Bai, Haoran Zhang +2

While autoregressive (AR) Vision-Language-Action (VLA) models have demonstrated formidable reasoning capabilities in robotic tasks, their sequential decoding process often incurs h…

cs.AI2026

Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling

Yafu Li, Runzhe Zhan, Haoran Zhang +25

Recent progress in reasoning models has substantially advanced long-horizon mathematical and scientific problem solving, with several systems now reaching gold-medal-level performa…

cs.RO2025

A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning

Shaopeng Zhai, Qi Zhang, Tianyi Zhang +7

Robotic real-world reinforcement learning (RL) with vision-language-action (VLA) models is bottlenecked by sparse, handcrafted rewards and inefficient exploration. We introduce VLA…