1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
【DL輪読会】1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal- more
カテゴリー: dls-2026
SOP: A Scalable Online Post-Training System for Vision-Language-Action Models
【DL輪読会】SOP: A Scalable Online Post-Training System for Vision-Language-Action Models more
Data Retrieval with Importance Weights for Few-Shot Imitation Learning
【DL輪読会】Data Retrieval with Importance Weights for Few-Shot Imitation Learning by @Dee more
Controlling Large Language Model with Latent Actions
【DL輪読会】Controlling Large Language Model with Latent Actions by @DeepLearning2023
Token Probabilities to Mitigate Large Language Models Overconfidence in Answering Medical Questions: Quantitative Study
【DL輪読会】Token Probabilities to Mitigate Large Language Models Overconfidence in Answer more
Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory
【DL輪読会】Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspe more
Pruning as a Game: Equilibrium-Driven Sparsification of Neural Networks
【DL輪読会】Pruning as a Game: Equilibrium-Driven Sparsification of Neural Networks by @De more
Pre-Trained Video Generative Models as World Simulators
【DL輪読会】Pre-Trained Video Generative Models as World Simulators by @DeepLearning2023
NFIG: Multi-Scale Autoregressive Image Generation via Frequency Ordering
【DL輪読会】NFIG: Multi-Scale Autoregressive Image Generation via Frequency Ordering by @D more