Geng, Xinyang

21 publications

ICLR 2025 Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning Amrith Setlur, Chirag Nagpal, Adam Fisch, Xinyang Geng, Jacob Eisenstein, Rishabh Agarwal, Alekh Agarwal, Jonathan Berant, Aviral Kumar
NeurIPS 2024 Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization Aniketh Janardhan Reddy, Xinyang Geng, Michael H. Herschl, Sathvik Kolli, Aviral Kumar, Patrick D. Hsu, Sergey Levine, Nilah M. Ioannidis
ICMLW 2024 Learning to Reason by Failing: Offline RL on Sub-Optimal Rollouts Scales Synthetic Data by 8x Amrith Setlur, Saurabh Garg, Xinyang Geng, Naman Garg, Virginia Smith, Aviral Kumar
NeurIPS 2024 RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold Amrith Setlur, Saurabh Garg, Xinyang Geng, Naman Garg, Virginia Smith, Aviral Kumar
CVPR 2024 Sequential Modeling Enables Scalable Learning for Large Vision Models Yutong Bai, Xinyang Geng, Karttikeya Mangalam, Amir Bar, Alan L. Yuille, Trevor Darrell, Jitendra Malik, Alexei A. Efros
ICLR 2024 The False Promise of Imitating Proprietary Language Models Arnav Gudibande, Eric Wallace, Charlie Victor Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, Dawn Song
CoRL 2023 Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning Jianlan Luo, Perry Dong, Jeffrey Wu, Aviral Kumar, Xinyang Geng, Sergey Levine
NeurIPSW 2023 Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction Han Qi, Stefano Rando, Xinyang Geng, Iku Ohama, Aviral Kumar, Sergey Levine
ICLRW 2023 Latent Conservative Objective Models for Offline Data-Driven Crystal Structure Prediction Han Qi, Stefano Rando, Xinyang Geng, Iku Ohama, Aviral Kumar, Sergey Levine
ICLR 2023 Offline Q-Learning on Diverse Multi-Task Data Both Scales and Generalizes Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine
ICLRW 2022 Data-Driven Optimization for Protein Design: Workflows, Algorithms and Metrics Sathvik Kolli, Amy X. Lu, Xinyang Geng, Aviral Kumar, Sergey Levine
ICML 2022 Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization Brandon Trabucco, Xinyang Geng, Aviral Kumar, Sergey Levine
ICMLW 2022 Effective Offline RL Needs Going Beyond Pessimism: Representations and Distributional Shift Xinyang Geng, Kevin Li, Abhishek Gupta, Aviral Kumar, Sergey Levine
ICMLW 2022 Multimodal Masked Autoencoders Learn Transferable Representations Xinyang Geng, Hao Liu, Lisa Lee, Dale Schuurmans, Sergey Levine, Pieter Abbeel
NeurIPSW 2022 Offline Q-Learning on Diverse Multi-Task Data Both Scales and Generalizes Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine
NeurIPSW 2022 Offline Q-Learning on Diverse Multi-Task Data Both Scales and Generalizes Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine
ICML 2021 Conservative Objective Models for Effective Offline Model-Based Optimization Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine
ICLR 2020 Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja, Sergey Levine
NeurIPS 2020 Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Ben Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov
ICMLW 2020 Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov
ICML 2018 Automatic Goal Generation for Reinforcement Learning Agents Carlos Florensa, David Held, Xinyang Geng, Pieter Abbeel