MDU minimizes forward KL divergence from prompt-conditional to prompt-masked unconditional predictions at masked positions to unlearn knowledge in MDLMs while trading off privacy and utility via temperature scaling.
Ddat: Diffusion policies enforcing dynamically admissible robot trajectories
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
SRDP infers process stages from multimodal observations to condition diffusion action generation and applies roughness-oriented constraints on process parameters for multi-stage robotic polishing.
X-Safe masks actions in configuration space using forward kinematics and quasi-static object models to give probabilistic collision-avoidance guarantees that transfer across robot embodiments without per-setup engineering.
SCP integrates diffusion-based imitation learning with Gaussian-encoded surface constraints and dynamic movement primitives to generate actions with improved success rates and contact stability on free-form surfaces.
citing papers explorer
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Machine Unlearning for Masked Diffusion Language Models
MDU minimizes forward KL divergence from prompt-conditional to prompt-masked unconditional predictions at masked positions to unlearn knowledge in MDLMs while trading off privacy and utility via temperature scaling.
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Stage-Aware and Roughness-Constrained Diffusion Policy for Multi-Stage Robotic Polishing
SRDP infers process stages from multimodal observations to condition diffusion action generation and applies roughness-oriented constraints on process parameters for multi-stage robotic polishing.
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Any-Body Guard: Universal Safeguarding for Manipulation Policies via Action Masking
X-Safe masks actions in configuration space using forward kinematics and quasi-static object models to give probabilistic collision-avoidance guarantees that transfer across robot embodiments without per-setup engineering.
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Surface Constraint Policy for Learning Surface-Constrained and Dynamically Feasible Robot Skills
SCP integrates diffusion-based imitation learning with Gaussian-encoded surface constraints and dynamic movement primitives to generate actions with improved success rates and contact stability on free-form surfaces.