3 papers
cs.RO2026
SynthDemo-RL: Breaking the Zero-Reward Barrier in VLA Adaptation with LLM-Guided Synthetic Demonstrations
Hiroaki Kingetsu, Hiroaki Kurihara, Kaoru Yokoo +2
Fine-tuning Vision-Language-Action (VLA) models commonly relies on human teleoperation demonstrations, while reinforcement learning (RL) with sparse binary rewards faces an explora…
cs.LG2025
Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models
Istabrak Abbes, Gopeshh Subbaraj, Matthew Riemer +6
Training large language models (LLMs) typically involves pre-training on massive corpora, only to restart the process entirely when new data becomes available. A more efficient and…
cs.LG2021
Neural Network Module Decomposition and Recomposition
Hiroaki Kingetsu, Kenichi Kobayashi, Taiji Suzuki
We propose a modularization method that decomposes a deep neural network (DNN) into small modules from a functionality perspective and recomposes them into a new model for some oth…