Publications

* below denotes equal contribution

2024

  1. Observational Scaling Laws and the Predictability of Language Model Performance
    Yangjun Ruan, Chris J Maddison, and Tatsunori Hashimoto
    In Advances in Neural Information Processing Systems (NeurIPS), 2024 [Spotlight]
  2. Graph-based Uncertainty Metrics for Long-form Language Model Outputs
    Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, and Tatsunori Hashimoto
    In Advances in Neural Information Processing Systems (NeurIPS), 2024 [Spotlight]
  3. Identifying the Risks of LM Agents with an LM-Emulated Sandbox
    Yangjun Ruan*, Honghua Dong*, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, and Tatsunori Hashimoto
    In International Conference on Learning Representations (ICLR), 2024 [Spotlight]

2023

  1. Calibrating Language Models via Augmented Prompt Ensembles
    Mingjian Jiang*, Yangjun Ruan*, Sicong Huang, Saifei Liao, Silviu Pitis, Roger Baker Grosse, and Jimmy Ba
    ICML Workshop on Deployment Challenges for Generative AI, 2023
  2. Weighted Ensemble Self-Supervised Learning
    Yangjun Ruan, Saurabh Singh, Warren Morningstar, Alexander A. Alemi, Sergey Ioffe, Ian Fischer, and Joshua V. Dillon
    In International Conference on Learning Representations (ICLR), 2023

2022

  1. Augment with Care: Contrastive Learning for the Boolean Satisfiability Problem
    Haonan Duan*, Pashootan Vaezipoor*, Max B Paulus, Yangjun Ruan, and Chris J Maddison
    In International Conference on Machine Learning (ICML), 2022
  2. Optimal Representations for Covariate Shift
    Yangjun Ruan*, Yann Dubois*, and Chris J Maddison
    In International Conference on Learning Representations (ICLR), 2022

2021

  1. Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
    Yangjun Ruan*, Karen Ullrich*, Daniel Severo*, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, and Chris J Maddison
    In International Conference on Machine Learning (ICML), 2021 [Oral]

2020

  1. Learning to Learn by Zeroth-Order Oracle
    Yangjun Ruan, Yuanhao Xiong, Sashank Reddi, Sanjiv Kumar, and Cho-Jui Hsieh
    In International Conference on Learning Representations (ICLR), 2020

2019

  1. FastSpeech: Fast, Robust and Controllable Text to Speech
    Yi Ren*, Yangjun Ruan*, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, and Tie-Yan Liu
    In Advances in Neural Information Processing Systems (NeurIPS), 2019
  2. Data transmission in mobile edge networks: Whether and where to compress?
    Jinke Ren*, Yangjun Ruan*, and Guanding Yu
    IEEE Communications Letters, 2019