Benchmarking Knowledge Transfer in Lifelong Robot Learning
Curated quantization research for VLA & WAM models β 180+ papers, a five-category taxonomy, a roadmap, and a companion PTQ + LIBERO toolkit (quant-vla).
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π A collection of utilities for LeRobot.
[LIBERO-MAX] A paired benchmark for robot-policy robustness to controlled changes introduced during execution.
Robot-agent harness with a CLI and local Web console for LIBERO short evaluation
Agent + reusable skill library for LIBERO manipulation tasks (no RL / VLA / world model; no LLM calls at runtime)
Turn world-model imagination into corrective training data for robot policies β a single-GPU, falsifiable pipeline (SmolVLA Β· LIBERO Β· CEM Β· paired simulator replays).
RadixQuantVLA is a unified, Lego-like framework for post-training quantization, benchmarking, and deployment preparation of Vision-Language-Action models, integrating QuantVLA, Omega-QVLA, OpenVLA, UniVLA, StarVLA, GR00T, and Pi0.5 routes with standardized launchers and validation on LIBERO benchmarks.
Fine-grained robot control with Jev, physics previews, and configurable LIBERO tasks.
Themeable React field of dots and lines that makes room around surfaces, with light that follows the pointer
Official implementation of PhaseLoRA: control-regime-conditioned low-rank adaptation for continuous-action vision-language-action policies, built on OpenPI.
WILRO-MoE: a small VLA for LIBERO, with golden-ticket noise search and deterministic noise cycles