Chen, Jianshu

21 publications

ICMLW 2024 RNR: Teaching Large Language Models to Follow Roles and Rules Kuan Wang, Alexander Bukharin, Haoming Jiang, Qingyu Yin, Zhengyang Wang, Tuo Zhao, Jingbo Shang, Chao Zhang, Bing Yin, Xian Li, Jianshu Chen, Shiyang Li

ICML 2024 Rewards-in-Context: Multi-Objective Alignment of Foundation Models with Dynamic Preference Adjustment Rui Yang, Xiaoman Pan, Feng Luo, Shuang Qiu, Han Zhong, Dong Yu, Jianshu Chen

AISTATS 2023 Blessing of Class Diversity in Pre-Training Yulai Zhao, Jianshu Chen, Simon Du

ICLR 2023 Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models Xiaoman Pan, Wenlin Yao, Hongming Zhang, Dian Yu, Dong Yu, Jianshu Chen

ICLR 2023 Learning Language Representations with Logical Inductive Bias Jianshu Chen

NeurIPS 2023 Thrust: Adaptively Propels Large Language Models with External Knowledge Xinran Zhao, Hongming Zhang, Xiaoman Pan, Wenlin Yao, Dong Yu, Jianshu Chen

ECCV 2020 Comprehensive Image Captioning via Scene Graph Decomposition Yiwu Zhong, Liwei Wang, Jianshu Chen, Dong Yu, Yin Li

ICLR 2020 TabFact: A Large-Scale Dataset for Table-Based Fact Verification Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang, Shiyang Li, Xiyou Zhou, William Yang Wang

ICLR 2020 Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search Anji Liu, Jianshu Chen, Mingze Yu, Yu Zhai, Xuewen Zhou, Ji Liu

AAAI 2019 Incorporating Structured Commonsense Knowledge in Story Completion Jiaao Chen, Jianshu Chen, Zhou Yu

NeurIPSW 2019 Learning to Recover Sparse Signals Sichen Zhong, Yue Zhao, Jianshu Chen

NeurIPS 2019 Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization Adithya M Devraj, Jianshu Chen

ICLR 2019 Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching Chih-Kuan Yeh, Jianshu Chen, Chengzhu Yu, Dong Yu

NeurIPS 2018 Coupled Variational Bayes via Optimization Embedding Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao, Le Song

NeurIPS 2018 M-Walk: Learning to Walk over Graphs Using Monte Carlo Tree Search Yelong Shen, Jianshu Chen, Po-Sen Huang, Yuqing Guo, Jianfeng Gao

ICML 2018 SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song

NeurIPS 2017 Q-LDA: Uncovering Latent Patterns in Text-Based Sequential Decision Processes Jianshu Chen, Chong Wang, Lin Xiao, Ji He, Lihong Li, Li Deng

ICML 2017 Stochastic Variance Reduction Methods for Policy Evaluation Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou

NeurIPS 2017 Unsupervised Sequence Classification Using Sequential Output Statistics Yu Liu, Jianshu Chen, Li Deng

NeurIPS 2015 End-to-End Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture Jianshu Chen, Ji He, Yelong Shen, Lin Xiao, Xiaodong He, Jianfeng Gao, Xinying Song, Li Deng

ICLR 2014 A New Method for Learning Deep Recurrent Neural Networks Jianshu Chen, Li Deng