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Found 5 papers, 1 papers with code
UniCode: Learning a Unified Codebook for Multimodal Large Language Models
In this paper, we propose \textbf{UniCode}, a novel approach within the domain of multimodal large language models (MLLMs) that learns a unified codebook to efficiently tokenize visual, text, and potentially other types of signals.
Towards General Computer Control: A Multimodal Agent for Red Dead Redemption II as a Case Study
Despite the success in specific tasks and scenarios, existing foundation agents, empowered by large models (LMs) and advanced tools, still cannot generalize to different scenarios, mainly due to dramatic differences in the observations and actions across scenarios.
Learning from Visual Observation via Offline Pretrained State-to-Go Transformer
Learning from visual observation (LfVO), aiming at recovering policies from only visual observation data, is promising yet a challenging problem.
GFIE: A Dataset and Baseline for Gaze-Following From 2D to 3D in Indoor Environments
Gaze-following is a kind of research that requires locating where the person in the scene is looking automatically under the topic of gaze estimation.
Distilling Neuron Spike with High Temperature in Reinforcement Learning Agents
This method uses distillation to effectively avoid the weakness of STBP, which can achieve SOTA performance in classification, and can obtain a smaller, faster convergence and lower power consumption SNN reinforcement learning model.
