Hao Liu

According to our database, Hao Liu authored at least 18 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Blockwise Parallel Transformer for Long Context Large Models.

Hao Liu, Pieter Abbeel

CoRR, 2023

The False Promise of Imitating Proprietary LLMs.

Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song

CoRR, 2023

Aligning Text-to-Image Models using Human Feedback.

Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Shixiang Shane Gu

CoRR, 2023

Chain of Hindsight Aligns Language Models with Feedback.

Hao Liu, Carmelo Sferrazza, Pieter Abbeel

CoRR, 2023

Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment.

Hao Liu, Wilson Yan, Pieter Abbeel

CoRR, 2023

Emergent Agentic Transformer from Chain of Hindsight Experience.

Hao Liu, Pieter Abbeel

Proceedings of the International Conference on Machine Learning, 2023

2022

FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners.

Hao Liu, Xinyang Geng, Lisa Lee, Igor Mordatch, Sergey Levine, Sharan Narang, Pieter Abbeel

CoRR, 2022

Instruction-Following Agents with Jointly Pre-Trained Vision-Language Models.

Hao Liu, Lisa Lee, Kimin Lee, Pieter Abbeel

CoRR, 2022

Multimodal Masked Autoencoders Learn Transferable Representations.

Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurams, Sergey Levine, Pieter Abbeel

CoRR, 2022

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery.

Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

CoRR, 2022

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

CoRR, 2022

Masked Autoencoding for Scalable and Generalizable Decision Making.

Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Unsupervised Reinforcement Learning with Contrastive Intrinsic Control.

Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Masked World Models for Visual Control.

Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel

Proceedings of the Conference on Robot Learning, 2022

2021

Behavior From the Void: Unsupervised Active Pre-Training.

Hao Liu, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

URLB: Unsupervised Reinforcement Learning Benchmark.

Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

APS: Active Pretraining with Successor Features.

Hao Liu, Pieter Abbeel

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Hybrid Discriminative-Generative Training via Contrastive Learning.

Hao Liu, Pieter Abbeel

CoRR, 2020