656 citations · 2.6k across the 58 of their papers we have counts for
6 papers · 1 filter
Emergence of Abstract State Representations in Embodied Sequence Modeling
Tian Yun, Zilai Zeng, Kunal Handa +4
Decision making via sequence modeling aims to mimic the success of language models, where actions taken by an embodied agent are modeled as tokens to predict. Despite their promisi…
Goal-Conditioned Predictive Coding for Offline Reinforcement Learning
Zilai Zeng, Ce Zhang, Shijie Wang +1
Recent work has demonstrated the effectiveness of formulating decision making as supervised learning on offline-collected trajectories. Powerful sequence models, such as GPT or BER…
Trajectory balance: Improved credit assignment in GFlowNets
Esmeralda S. Whitammer, Moksh Jain, Emmanuel Bengio +2
Generative flow networks (GFlowNets) are a method for learning a stochastic policy for generating compositional objects, such as graphs or strings, from a given unnormalized densit…
Discrete-Valued Neural Communication
Dianbo Liu, Alex Lamb, Kenji Kawaguchi +4
Deep learning has advanced from fully connected architectures to structured models organized into components, e.g., the transformer composed of positional elements, modular archite…
Learning Video Representations using Contrastive Bidirectional Transformer
Chen Sun, Fabien Baradel, Kevin Murphy +1
This paper proposes a self-supervised learning approach for video features that results in significantly improved performance on downstream tasks (such as video classification, cap…
Stochastic Prediction of Multi-Agent Interactions from Partial Observations
Chen Sun, Per Karlsson, Jiajun Wu +2
We present a method that learns to integrate temporal information, from a learned dynamics model, with ambiguous visual information, from a learned vision model, in the context of…