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Found 6 papers, 3 papers with code
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining
A rich representation is key to general robotic manipulation, but existing approaches to representation learning require large amounts of multimodal demonstrations.
Relational Attention: Generalizing Transformers for Graph-Structured Tasks
Transformers flexibly operate over sets of real-valued vectors representing task-specific entities and their attributes, where each vector might encode one word-piece token and its position in a sequence, or some piece of information that carries no position at all.
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
We demonstrate the utility of MoCapAct by using it to train a single hierarchical policy capable of tracking the entire MoCap dataset within dm_control and show the learned low-level component can be re-used to efficiently learn downstream high-level tasks.
Working Memory Graphs
Transformers have increasingly outperformed gated RNNs in obtaining new state-of-the-art results on supervised tasks involving text sequences.
NAIL: A General Interactive Fiction Agent
Interactive Fiction (IF) games are complex textual decision making problems.
Now I Remember! Episodic Memory For Reinforcement Learning
Humans rely on episodic memory constantly, in remembering the name of someone they met 10 minutes ago, the plot of a movie as it unfolds, or where they parked the car.
