ElasticTok: Adaptive Tokenization for Image and Video
Wilson Yan, Matei Zaharia, Volodymyr Mnih, Pieter Abbeel, Aleksandra Faust, Hao Liu
Arxiv, 2024
[paper, code, project, tl;dr]

World Model on Million-Length Video And Language With Blockwise RingAttention
Hao Liu*, Wilson Yan*, Matei Zaharia, Pieter Abbeel
Arxiv, 2024
[paper, code, project, tl;dr]

Ring Attention with Blockwise Transformers for Near-Infinite Context
Hao Liu, Matei Zaharia, Pieter Abbeel
International Conference on Learning Representations(ICLR), 2024
[paper, code, media, tl;dr]

Blockwise Parallel Transformer for Large Context Models
Hao Liu, Pieter Abbeel
Advances in Neural Information Processing Systems(NeurIPS)(Spotlight Presentation), 2023
[paper, code, tl;dr]

Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment
Hao Liu, Wilson Yan, Pieter Abbeel
Advances in Neural Information Processing Systems(NeurIPS), 2023
[paper, code, tl;dr]

Chain of Hindsight Aligns Language Models with Feedback
Hao Liu, Carmelo Sferrazza, Pieter Abbeel
International Conference on Learning Representations(ICLR), 2024
[paper, code, tl;dr]

Emergent Agentic Transformer from Chain of Hindsight Experience
Hao Liu, Pieter Abbeel
International Conference on Machine Learning(ICML), 2023
[paper, tl;dr]

Koala: A dialogue model for academic research
Xinyang Geng*, Arnav Gudibande*, Hao Liu*, Eric Wallace*, Pieter Abbeel†, Sergey Levine†, Dawn Song†.
Blog, 2023
[blog]

OpenLLaMa, an open reproduction of LLaMA
Xinyang Geng*, Hao Liu*.
GitHub, 2023
[code, tl;dr]

Masked Autoencoding for Scalable and Generalizable Decision Making
Fangchen Liu*, Hao Liu*, Aditya Grover, Pieter Abbeel
Advances in Neural Information Processing Systems(NeurIPS), 2022
[paper, code, tl;dr]

Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning
Denis Yarats*, David Brandfonbrener*, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto
Arxiv, 2022
[paper, code, tl;dr]

Multimodal Masked Autoencoders Learn Transferable Representations
Xinyang Geng*, Hao Liu*, Lisa Lee, Dale Schuurmans, Sergey Levine, Pieter Abbeel
ICML Pre-training Workshop (Oral Presentation), 2022.
[paper, code, tl;dr]

Palm up: Playing in the Latent Manifold for Unsupervised Pretraining
Hao Liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh
Advances in Neural Information Processing Systems(NeurIPS), 2022
[paper, tl;dr]

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery
Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel
Advances in Neural Information Processing Systems(NeurIPS), 2022
[paper, project]

URLB: Unsupervised Reinforcement Learning Benchmark.
Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang,
Lerrel Pinto, Pieter Abbeel
NeurIPS 2021 Track Datasets and Benchmarks, 2021
[paper, code, tl;dr]

APS: Active Pre-Training with Successor Features
Hao Liu, Pieter Abbeel
International Conference on Machine Learning(ICML)(Long Oral Presentation), 2021.
[paper, code]

Behavior From the Void: Unsupervised Active Pre-Training
Hao Liu, Pieter Abbeel
Advances in Neural Information Processing Systems(NeurIPS)(Spotlight Presentation), 2021.
[paper, code, tl;dr]

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