Publications

Peer-Reviewed Papers

• Radar: Fast Long-Context Decoding for Any Transformer
  Yongchang Hao, Mengyao Zhai, Hossein Hajimirsadeghi, Sepidehsadat Hosseini, Frederick Tung
  ICLR 2025, Singapore
• Exploiting the Index Gradients for Optimization-Based Jailbreaking on Large Language Models Jiahui Li*, Yongchang Hao*, Haoyu Xu, Xing Wang, Yu Hong
  COLING 2025, Dubai, U.A.E.
• NeuZip: Memory-Efficient Training and Inference with Dynamic Compression of Neural Networks
  Yongchang Hao, Yanshuai Cao, Lili Mou
  ENLSP @ NeurIPS 2024, Vancouver, Canada
• Flora: Low-Rank Adapters Are Secretly Gradient Compressors
  Yongchang Hao, Yanshuai Cao, Lili Mou
  ICML 2024, Vienna, Austria
• LLMR: Knowledge Distillation with a Large Language Model-Induced Reward
  Dongheng Li, Yongchang Hao, Lili Mou
  COLING 2024, Turin, Italy
• An Equal-Size Hard EM Algorithm for Diverse Dialogue Generation
  Yuqiao Wen, Yongchang Hao, Yanshuai Cao, Lili Mou
  ICLR 2023, Kigali, Rwanda
• Teacher Forcing Recovers Reward Functions for Text Generation
  Yongchang Hao, Yuxin Liu, Lili Mou
  NeurIPS 2022, New Orleans, U.S.A.
• Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation
  Wenxuan Wang, Wenxiang Jiao, Yongchang Hao, Xing Wang, Shuming Shi, Zhaopeng Tu, Michael Lyu
  ACL 2022, Dublin, Ireland
• Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation
  Yongchang Hao*, Shilin He*, Wenxiang Jiao, Zhaopeng Tu, Michael Lyu, Xing Wang
  NAACL 2021, Online

Preprints

• ULPT: Prompt Tuning with Ultra-Low-Dimensional Optimization
  Zijun Wu, Yongchang Hao, Lili Mou
  ar$\chi$iv 2025
• Ginger: An Efficient Curvature Approximation with Linear Complexity for General Neural Networks
  Yongchang Hao, Yanshuai Cao, Lili Mou
  ar$\chi$iv 2024

Theses

• Discovering Reward Functions for Language Models
  Yongchang Hao
  M.Sc. Thesis, University of Alberta, 2023