51 citations · 183 across the 17 of their papers we have counts for
4 papers · 1 filter
Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes
Aviral Kumar, Rishabh Agarwal, Xinyang Geng +2
The potential of offline reinforcement learning (RL) is that high-capacity models trained on large, heterogeneous datasets can lead to agents that generalize broadly, analogously t…
Towards Better Few-Shot and Finetuning Performance with Forgetful Causal Language Models
Hao Liu, Xinyang Geng, Lisa Lee +4
Large language models (LLM) trained using the next-token-prediction objective, such as GPT3 and PaLM, have revolutionized natural language processing in recent years by showing imp…
Multimodal Masked Autoencoders Learn Transferable Representations
Xinyang Geng, Hao Liu, Lisa Lee +3
Building scalable models to learn from diverse, multimodal data remains an open challenge. For vision-language data, the dominant approaches are based on contrastive learning objec…
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization
Brandon Trabucco, Xinyang Geng, Aviral Kumar +1
Black-box model-based optimization (MBO) problems, where the goal is to find a design input that maximizes an unknown objective function, are ubiquitous in a wide range of domains,…