A VLA policy using view-selective visual routing and interaction-aware action MoE improves average success by 27.7% in simulation and 43.3% in real-world bimanual tasks over monolithic baselines.
Skillvla: Tackling combinatorial diversity in dual-arm manipulation via skill reuse
4 Pith papers cite this work. Polarity classification is still indexing.
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TAMEn supplies a cross-morphology wearable interface and pyramid-structured visuo-tactile data regime that raises bimanual manipulation success rates from 34% to 75% via closed-loop collection.
ReuseRL augments agentic RL with an MDL-based compression penalty on skill reuse, proves a PAC-Bayes bound, and reports higher in- and out-of-distribution success on ALFWorld, TextWorld-Cooking, and Countdown-Stepwise versus GRPO and round-length baselines.
A survey that organizes existing work on LLM-based agents around code as the central harness, structured in three layers of interfaces, mechanisms, and multi-agent scaling, with applications across domains and listed open challenges.
citing papers explorer
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See Selectively, Act Adaptively: Dual-Level Structural Decomposition for Bimanual Robot Manipulation
A VLA policy using view-selective visual routing and interaction-aware action MoE improves average success by 27.7% in simulation and 43.3% in real-world bimanual tasks over monolithic baselines.
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TAMEn: Tactile-Aware Manipulation Engine for Closed-Loop Data Collection in Contact-Rich Tasks
TAMEn supplies a cross-morphology wearable interface and pyramid-structured visuo-tactile data regime that raises bimanual manipulation success rates from 34% to 75% via closed-loop collection.
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Skill Reuse as Compression in Agentic RL
ReuseRL augments agentic RL with an MDL-based compression penalty on skill reuse, proves a PAC-Bayes bound, and reports higher in- and out-of-distribution success on ALFWorld, TextWorld-Cooking, and Countdown-Stepwise versus GRPO and round-length baselines.
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Code as Agent Harness
A survey that organizes existing work on LLM-based agents around code as the central harness, structured in three layers of interfaces, mechanisms, and multi-agent scaling, with applications across domains and listed open challenges.