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Total papers: 7 Search mode: keyword Shortlist (0) RSS

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Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Qiuyue Wang, Mingsheng Li, Jian Guan, Jinhui Ye, Sicheng Xie, Yitao Liu · May 28, 2026

Citations: 0

Match reason: Matches selected tags (Long Horizon, General).

Score: 58% Moderate protocol signal Freshness: Warm Status: Ready
Demonstrations Simulation Env Long Horizon General
  • Qwen-VLA is trained with a large-scale joint pretraining recipe over diverse data sources, including robotics manipulation trajectories, human egocentric demonstrations, synthetic simulation data, vision-and-language navigation data,…
  • Experiments on manipulation, navigation, and trajectory-centric benchmarks show consistent multi-task performance and out-of-distribution generalization under variations in scene layout, background, lighting, object configuration, and robot…
Open paper

Match reason: Matches selected tags (Long Horizon, General).

Score: 58% High protocol signal Freshness: Warm Status: Ready
Demonstrations Human EvalLlm As Judge Long Horizon General
  • LLM agents fail on the majority of real-world tasks -- GPT-4o succeeds on fewer than 15% of WebArena navigation tasks and below 55% pass@1 on ToolBench (Zhou et al., 2024; Qin et al., 2024) -- yet every failed trajectory is routinely…
  • We introduce AgentHER, a framework that recovers this lost training signal by adapting the Hindsight Experience Replay (HER; Andrychowicz et al., 2017) principle to natural-language agent trajectories for offline data augmentation.
Open paper
MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile Manipulation

Chengshu Li, Mengdi Xu, Arpit Bahety, Hang Yin, Yunfan Jiang, Huang Huang · Oct 21, 2025

Citations: 0

Match reason: Matches selected tags (Long Horizon, General).

Score: 53% Moderate protocol signal Freshness: Cold Status: Ready
Demonstrations Simulation Env Long Horizon General
  • Imitation learning from large-scale, diverse human demonstrations has been shown to be effective for training robots, but collecting such data is costly and time-consuming.
  • This challenge intensifies for multi-step bimanual mobile manipulation, where humans must teleoperate both the mobile base and two high-DoF arms.
Open paper
Watch and Learn: Learning to Use Computers from Online Videos

Chan Hee Song, Yiwen Song, Palash Goyal, Yu Su, Oriana Riva, Hamid Palangi · Oct 6, 2025

Citations: 0

Match reason: Matches selected tags (Long Horizon, General).

Score: 53% Moderate protocol signal Freshness: Cold Status: Ready
Demonstrations Long Horizon General
  • Computer-using agents (CUAs) must plan task workflows across diverse and evolving applications, yet progress is limited by the lack of large-scale, high-quality training data.
  • We present Watch & Learn (W&L), a framework that converts readily available Internet videos of human computer use into executable UI trajectories at scale.
Open paper
Mastering Multi-Drone Volleyball through Hierarchical Co-Self-Play Reinforcement Learning

Ruize Zhang, Sirui Xiang, Zelai Xu, Feng Gao, Shilong Ji, Wenhao Tang · May 7, 2025

Citations: 0

Match reason: Matches selected tags (Long Horizon, General).

Score: 53% High protocol signal Freshness: Cold Status: Ready
Demonstrations Automatic Metrics Long Horizon General
  • The task is turn-based, multi-agent, and physically grounded, posing significant challenges due to its long-horizon dependencies, tight inter-agent coupling, and the underactuated dynamics of quadrotors.
Open paper
IROSA: Interactive Robot Skill Adaptation using Natural Language

Markus Knauer, Samuel Bustamante, Thomas Eiband, Alin Albu-Schäffer, Freek Stulp, João Silvério · Mar 4, 2026

Citations: 0

Match reason: Matches selected tags (Long Horizon, General).

Score: 50% Moderate protocol signal Freshness: Cold Status: Ready
Demonstrations Long Horizon General
  • We demonstrate the framework on a 7-DoF torque-controlled robot performing an industrial bearing ring insertion task, showing successful skill adaptation through natural language commands for speed adjustment, trajectory correction, and…
Open paper

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