Learning Transformer-based World Models with Contrastive Predictive Coding
【DL輪読会】Learning Transformer-based World Models with Contrastive Predictive Coding by more
カテゴリー: papers
Learning from video: how to leverage the no-action label video data
【DL輪読会】Learning from video: how to leverage the no-action label video data by @DeepLe more
Real-Time Execution of Action Chunking Flow Policies
【DL輪読会】Real-Time Execution of Action Chunking Flow Policies by @DeepLearning2023
DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Models
【DL輪読会】DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using more
Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation
【DL輪読会】Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulatio more
Titans: Learning to Memorize at Test Time
【DL輪読会】 Titans: Learning to Memorize at Test Time by @DeepLearning2023
Towards Understanding How Knowledge Evolves in Large Vision-Language Models
【DL輪読会】Towards Understanding How Knowledge Evolves in Large Vision-Language Models by more
Language Models Are Capable of Metacognitive Monitoring and Control of Their Internal Activations
【DL輪読会】 Language Models Are Capable of Metacognitive Monitoring and Control of Their more
A continuous time framework for discrete denoising models
【Diffusion勉強会】A continuous time framework for discrete denoising models by @DeepLearn more
From task structures to world models: what do LLMs know?
【DL輪読会】From task structures to world models: what do LLMs know? by @DeepLearning2023