GRASP maps natural language to bounding-box goals via VLM for neuro-symbolic planning and reports 73.3% success in 90 real-robot trials without task-specific training.
LoHoRavens: A Long-Horizon Language- Conditioned Benchmark for Robotic Tabletop Manipulation,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
ExS2D is a hierarchical framework that expands single-arm supervision into dual-arm executions via subtask decomposition, guided mapping, and precedence-aware LLM planning, cutting steps by 54.4% in simulation.
citing papers explorer
-
Bounding Boxes as Goals: Language-Conditioned Grasping via Neuro-Symbolic Planning
GRASP maps natural language to bounding-box goals via VLM for neuro-symbolic planning and reports 73.3% success in 90 real-robot trials without task-specific training.
-
One-to-Two Acting: A Novel Framework for Single-arm Agent Action Expansion to Dual Arms
ExS2D is a hierarchical framework that expands single-arm supervision into dual-arm executions via subtask decomposition, guided mapping, and precedence-aware LLM planning, cutting steps by 54.4% in simulation.