Nan Jiang

Can Language Models Replace Programmers for Coding? REPOCOD Says ‘Not Yet’ ACL 2025 Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning ICLR 2025 DART: Distilling Autoregressive Reasoning to Silent Thought EMNLP 2025 Commit0: Library Generation from Scratch ICLR 2025 WAFFLE: Fine-tuning Multi-Modal Model for Automated Front-End Development ACL 2025 MLLM-as-a-Judge for Image Safety without Human Labeling CVPR 2025 Dynamic Motion Blending for Versatile Motion Editing CVPR 2025 GameArena: Evaluating LLM Reasoning through Live Computer Games ICLR 2025 Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching AAAI 2025 Statistical Tractability of Off-policy Evaluation of History-dependent Policies in POMDPs ICLR 2025 Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning ICLR 2025 LATTE: Improving Latex Recognition for Tables and Formulae with Iterative Refinement AAAI 2025 Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits ICML 2025 Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment ICML 2025 Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability ICLR 2024 Mitigating the Alignment Tax of RLHF EMNLP 2024 Scaling Up Dynamic Human-Scene Interaction Modeling CVPR 2024 F-HOI: Toward Fine-grained Semantic-Aligned 3D Human-Object Interactions ECCV 2024 Model-Free Representation Learning and Exploration in Low-Rank MDPs JMLR 2024 Vertical Symbolic Regression via Deep Policy Gradient IJCAI 2024 Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality NIPS 2024 PhyRecon: Physically Plausible Neural Scene Reconstruction NIPS 2024 LeDex: Training LLMs to Better Self-Debug and Explain Code NIPS 2024 Online Iterative Reinforcement Learning from Human Feedback with General Preference Model NIPS 2024 On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation NIPS 2024 Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity NIPS 2024 Racing Control Variable Genetic Programming for Symbolic Regression AAAI 2024 Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration with Provable Guarantees AAAI 2024 Word Embeddings Are Steers for Language Models ACL 2024 Harnessing Density Ratios for Online Reinforcement Learning ICLR 2024 Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint ICML 2024 The Role of Coverage in Online Reinforcement Learning ICLR 2023 Adversarial Model for Offline Reinforcement Learning NIPS 2023 The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation ICML 2023 Reinforcement Learning in Low-rank MDPs with Density Features ICML 2023 Offline Learning in Markov Games with General Function Approximation ICML 2023 Explaining RL Decisions with Trajectories ICLR 2023 Full-Body Articulated Human-Object Interaction ICCV 2023 Learning Markov Random Fields for Combinatorial Structures via Sampling through Lovász Local Lemma AAAI 2023 Marginalized Importance Sampling for Off-Environment Policy Evaluation CORL 2023 Future-Dependent Value-Based Off-Policy Evaluation in POMDPs NIPS 2023 Interaction-Grounded Learning with Action-Inclusive Feedback NIPS 2022 Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret NIPS 2022 Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions NIPS 2022 On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL NIPS 2022 A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation NIPS 2022 On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio Correction AISTATS 2022 Offline Reinforcement Learning with Realizability and Single-policy Concentrability COLT 2022 Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality ICLR 2022 Adversarially Trained Actor Critic for Offline Reinforcement Learning ICML 2022 A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes ICML 2022 Constraint Reasoning Embedded Structured Prediction JMLR 2022 Offline reinforcement learning under value and density-ratio realizability: The power of gaps UAI 2022 Bellman-consistent Pessimism for Offline Reinforcement Learning NIPS 2021 Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration AAAI 2021 On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function COLT 2021 Minimax Model Learning AISTATS 2021 Batch Value-function Approximation with Only Realizability ICML 2021 PALM: Probabilistic area loss Minimization for Protein Sequence Alignment UAI 2021 Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning NIPS 2021 Towards Hyperparameter-free Policy Selection for Offline Reinforcement Learning NIPS 2021 RL-Duet: Online Music Accompaniment Generation Using Deep Reinforcement Learning AAAI 2020 Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach EMNLP 2020 Scale Match for Tiny Person Detection WACV 2020 Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles AISTATS 2020 A Question Type Driven and Copy Loss Enhanced Frameworkfor Answer-Agnostic Neural Question Generation ACL 2020 From Importance Sampling to Doubly Robust Policy Gradient ICML 2020 Minimax Weight and Q-Function Learning for Off-Policy Evaluation ICML 2020 Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison UAI 2020 When Counterpoint Meets Chinese Folk Melodies NIPS 2020 Minimax Value Interval for Off-Policy Evaluation and Policy Optimization NIPS 2020 Provably Efficient Q-Learning with Low Switching Cost NIPS 2019 Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches COLT 2019 Information-Theoretic Considerations in Batch Reinforcement Learning ICML 2019 Provably efficient RL with Rich Observations via Latent State Decoding ICML 2019 LSDSCC: a Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics NAACL 2018 Markov Decision Processes with Continuous Side Information ALT 2018 Hierarchical Imitation and Reinforcement Learning ICML 2018 On Oracle-Efficient PAC RL with Rich Observations NIPS 2018 Completing State Representations using Spectral Learning NIPS 2018 Open Problem: The Dependence of Sample Complexity Lower Bounds on Planning Horizon COLT 2018 Exploration of Tree-based Hierarchical Softmax for Recurrent Language Models IJCAI 2017 Contextual Decision Processes with low Bellman rank are PAC-Learnable ICML 2017 Repeated Inverse Reinforcement Learning NIPS 2017 The Dependence of Effective Planning Horizon on Model Accuracy IJCAI 2016 Doubly Robust Off-policy Value Evaluation for Reinforcement Learning ICML 2016 On Structural Properties of MDPs that Bound Loss Due to Shallow Planning IJCAI 2016 Abstraction Selection in Model-based Reinforcement Learning ICML 2015 Low-Rank Spectral Learning with Weighted Loss Functions AISTATS 2015 Unifying Spatial and Attribute Selection for Distracter-Resilient Tracking CVPR 2014