arXiv (All)
open access
Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline)
I describe my solution to the LeHome Challenge 2026, an ICRA 2026 competition on bimanual garment folding. The system placed 1st of 62 teams in the online (simulation) round and 2nd in the real-world final. It improves a vision-language-action (VLA) policy with a reinforcement-learning loop. The pol
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline)#310824
- EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models#630018
- EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models#628156
- Damage-Aware Bandit Pruning for Vision and Language Transformers#972512
- RedFlow: Redirect Failure into Action-level Corrections for Flow-matching VLA Policy#1118671
Record · ID 1048718
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive