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π0: A Vision-Language-Action Flow Model for General Robot Control
π0 is a vision-language-action flow model that enables general, dexterous robot control across diverse robotic platforms.
Reinforcement Learning Enables Scaling Generalist Robot Policy Improvement
Reinforcement learning enables generalist robot policies to simultaneously improve across multiple diverse tasks.
ConInstruct: Evaluating Large Language Models on Conflict Detection and Resolution in Instructions
ConInstruct evaluates how large language models detect and resolve conflicting constraints in user prompts.
Vision Language Action Models in Robotic Manipulation: A Systematic Review
A comprehensive review of 102 Vision Language Action models, foundational datasets, and simulators for robotic manipulation.
Reverse Engineering Structure and Semantics of Input of a Binary Executable
Recover binary input formats and semantic field relations using dynamic taint analysis.
Learning Deployable Locomotion Control via Differentiable Simulation
First successful sim-to-real transfer of legged locomotion learned via differentiable simulation using a novel contact model.
Useful Memories Become Faulty When Continuously Updated by LLMs
Continuously updated LLM consolidated memories degrade over time, often falling below no-memory baselines.
Robotic Data Inoculation
Data Inoculation uses a residual policy during teleoperation to actively expose robots to failure states and collect recovery data.
BGPFuzz: Automated Configuration Fuzzing of the Border Gateway Protocol
BGPFuzz is a stateful fuzzing framework that automatically discovers BGP routing misconfigurations using virtualized network testbeds.
Exploring the Potential of QEEGNet for Cross-Task and Cross-Dataset Electroencephalography Encoding with Quantum Machine Learning
We evaluate QEEGNet, a hybrid quantum-classical neural network, for cross-dataset EEG decoding and generalization.
METATRON: A Promptable Whole-Body Execution Layer for Humanoids
Metatron is a promptable whole-body execution layer that unifies humanoid control through a frozen base policy and programmable skills.
Local Budget Benefits, Population Commitment, and Solver Performance: A DGO Case Study with Controlled DE Transfer
This paper introduces Da Gou Gun Optimization (DGO) to analyze local search benefits, population commitment, and overall solver performance.
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