Tongran Liu

According to our database, Tongran Liu authored at least 23 papers between 2013 and 2026.

Collaborative distances:

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

2026

SPS: Steering Probability Squeezing for Better Exploration in Reinforcement Learning for Large Language Models.

Yifu Huo, Chenglong Wang, Ziming Zhu, Shunjie Xing, Peinan Feng, Tongran Liu, Qiaozhi He, Tianhua Zhou, Xiaojia Chang, Jingbo Zhu, Zhengtao Yu, Tong Xiao

CoRR, April, 2026

The effects of working memory and interference control on reinforcement learning: Evidence from computational modeling and structural MRI.

Mengxin Wen, Chengyan Yang, Tongran Liu, Kristoffer H. Madsen, Xun Liu

NeuroImage, 2026

Probing Preference Representations: A Multi-Dimensional Evaluation and Analysis Method for Reward Models.

Chenglong Wang, Yifu Huo, Yang Gan, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Chunliang Zhang, Tongran Liu, Anxiang Ma, Zhengtao Yu, Jingbo Zhu, Tong Xiao

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

MRO: Enhancing Reasoning in Diffusion Language Models via Multi-Reward Optimization.

Chenglong Wang, Yang Gan, Hang Zhou, Chi Hu, Yongyu Mu, Kai Song, Murun Yang, Bei Li, Chunliang Zhang, Tongran Liu, Jingbo Zhu, Zhengtao Yu, Tong Xiao

CoRR, October, 2025

HEAL: A Hypothesis-Based Preference-Aware Analysis Framework.

Yifu Huo, Chenglong Wang, Qiren Zhu, Shunjie Xing, Tong Xiao, Chunliang Zhang, Tongran Liu, Jinbo Zhu

CoRR, August, 2025

GRAM: A Generative Foundation Reward Model for Reward Generalization.

Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Qiaozhi He, Murun Yang, Bei Li, Tong Xiao, Chunliang Zhang, Tongran Liu, JingBo Zhu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

HEAL: A Hypothesis-Based Preference-Aware Analysis Framework.

Yifu Huo, Chenglong Wang, Qiren Zhu, Shunjie Xing, Tong Xiao, Chunliang Zhang, Tongran Liu, JingBo Zhu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

RoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data.

Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Murun Yang, Qiaozhi He, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

LRHP: Learning Representations for Human Preferences via Preference Pairs.

Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Qiaozhi He, Murun Yang, Tong Xiao, Chunliang Zhang, Tongran Liu, Jingbo Zhu

CoRR, 2024

RoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data.

Chenglong Wang, Yang Gan, Yifu Huo, Yongyu Mu, Murun Yang, Qiaozhi He, Tong Xiao, Chunliang Zhang, Tongran Liu, Quan Du, Di Yang, Jingbo Zhu

CoRR, 2024

Large Language Models are Parallel Multilingual Learners.

Yongyu Mu, Peinan Feng, Zhiquan Cao, Yuzhang Wu, Bei Li, Chenglong Wang, Tong Xiao, Kai Song, Tongran Liu, Chunliang Zhang, Jingbo Zhu

CoRR, 2024

Revealing the Parallel Multilingual Learning within Large Language Models.

Yongyu Mu, Peinan Feng, Zhiquan Cao, Yuzhang Wu, Bei Li, Chenglong Wang, Tong Xiao, Kai Song, Tongran Liu, Chunliang Zhang, JingBo Zhu

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Hybrid Alignment Training for Large Language Models.

Chenglong Wang, Hang Zhou, Kaiyan Chang, Bei Li, Yongyu Mu, Tong Xiao, Tongran Liu, JingBo Zhu

Proceedings of the Findings of the Association for Computational Linguistics, 2024

ESRL: Efficient Sampling-Based Reinforcement Learning for Sequence Generation.

Chenglong Wang, Hang Zhou, Yimin Hu, Yifu Huo, Bei Li, Tongran Liu, Tong Xiao, Jingbo Zhu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Learning Evaluation Models from Large Language Models for Sequence Generation.

Chenglong Wang, Hang Zhou, Kaiyan Chang, Tongran Liu, Chunliang Zhang, Quan Du, Tong Xiao, Jingbo Zhu

CoRR, 2023

2020

Towards Fully 8-bit Integer Inference for the Transformer Model.

Ye Lin, Yanyang Li, Tengbo Liu, Tong Xiao, Tongran Liu, Jingbo Zhu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Does Multi-Encoder Help? A Case Study on Context-Aware Neural Machine Translation.

Bei Li, Hui Liu, Ziyang Wang, Yufan Jiang, Tong Xiao, Jingbo Zhu, Tongran Liu, Changliang Li

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Learning Architectures from an Extended Search Space for Language Modeling.

Yinqiao Li, Chi Hu, Yuhao Zhang, Nuo Xu, Yufan Jiang, Tong Xiao, Jingbo Zhu, Tongran Liu, Changliang Li

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Neural Machine Translation with Joint Representation.

Yanyang Li, Qiang Wang, Tong Xiao, Tongran Liu, Jingbo Zhu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Sharing Attention Weights for Fast Transformer.

Tong Xiao, Yinqiao Li, Jingbo Zhu, Zhengtao Yu, Tongran Liu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2017

Fast Parallel Training of Neural Language Models.

Tong Xiao, Jingbo Zhu, Tongran Liu, Chunliang Zhang

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Syntactic Skeleton-Based Translation.

Tong Xiao, Jingbo Zhu, Chunliang Zhang, Tongran Liu

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2013

Bagging and Boosting statistical machine translation systems.

Tong Xiao, Jingbo Zhu, Tongran Liu

Artif. Intell., 2013