Han Liu

PromptFE: Automated Feature Engineering by Prompting EACL 2026 ProgressLM: Towards Progress Reasoning in Vision-Language Models ACL 2026 MRT: Learning Compact Representations with Mixed RWKV-Transformer for Extreme Image Compression AAAI 2026 Efficient Paths and Dense Rewards: Probabilistic Flow Reasoning for Large Language Models ACL 2026 TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval ACL 2026 MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization ACL 2026 BiO-HMC: Dynamic Human-Machine Collaboration for Consensus Decision-Making via Bilevel Optimization AAAI 2026 A Survey of Large Language Models for Text-Guided Molecular Discovery: From Molecule Generation to Optimization ACL 2026 KnowLCP: Knowledge Augmented Lane Change Prediction for Autonomous Driving AAAI 2026 DS2-Instruct: Domain-Specific Data Synthesis for Large Language Models Instruction Tuning EACL 2026 On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality ICLR 2025 Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency ICLR 2025 AdaDHP: Fine-Grained Fine-Tuning via Dual Hadamard Product and Adaptive Parameter Selection ACL 2025 Shadow-Activated Backdoor Attacks on Multimodal Large Language Models ACL 2025 EcoLoRA: Communication-Efficient Federated Fine-Tuning of Large Language Models EMNLP 2025 SEP-MLDC: A Simple and Effective Paradigm for Multi-Label Document Classification NAACL 2025 Pairwise Prompt-Based Tuning with Parameter Efficient Fast Adaptation for Generalized Zero-Shot Intent Detection NAACL 2025 A Non-contrast Head CT Foundation Model for Comprehensive Neuro-Trauma Triage MICCAI 2025 Improving Accuracy and Calibration via Differentiated Deep Mutual Learning CVPR 2025 Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory AISTATS 2025 ECG2TOK: ECG Pre-Training with Self-Distillation Semantic Tokenizers IJCAI 2025 In-Context Deep Learning via Transformer Models ICML 2025 In-Context Learning as Conditioned Associative Memory Retrieval ICML 2025 Fast and Low-Cost Genomic Foundation Models via Outlier Removal ICML 2025 Nonparametric Modern Hopfield Models ICML 2025 Dual-View Interaction-Aware Lane Change Prediction for Autonomous Driving AAAI 2025 Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models ICLR 2025 Computational Limits of Low-Rank Adaptation (LoRA) Fine-Tuning for Transformer Models ICLR 2025 EGSRAL:An Enhanced 3D Gaussian Splatting Based Renderer with Automated Labeling for Large-Scale Driving Scene AAAI 2025 Multi-Label Few-Shot Image Classification via Pairwise Feature Augmentation and Flexible Prompt Learning AAAI 2025 Uncertainty-Aware Contrastive Learning with Hard Negative Sampling for Code Search Tasks AAAI 2025 PRISM: A Promptable and Robust Interactive Segmentation Model with Visual Prompts MICCAI 2024 BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models EMNLP 2024 EIVEN: Efficient Implicit Attribute Value Extraction using Multimodal LLM NAACL 2024 Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints ICLR 2024 STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction ICLR 2024 SELP: A Semantically-Driven Approach for Separated and Accurate Class Prototypes in Few-Shot Text Classification ACL 2024 Global Convergence in Training Large-Scale Transformers NIPS 2024 On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs) NIPS 2024 Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes NIPS 2024 One-Layer Transformer Provably Learns One-Nearest Neighbor In Context NIPS 2024 A Coarse-to-Fine Prototype Learning Approach for Multi-Label Few-Shot Intent Detection EMNLP 2024 Let’s Ask GNN: Empowering Large Language Model for Graph In-Context Learning EMNLP 2024 Sequential LLM Framework for Fashion Recommendation EMNLP 2024 Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing AAAI 2024 A Goal Interaction Graph Planning Framework for Conversational Recommendation AAAI 2024 Depression Detection via Capsule Networks with Contrastive Learning AAAI 2024 DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes ICLR 2024 Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees AISTATS 2024 On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis ICML 2024 Outlier-Efficient Hopfield Layers for Large Transformer-Based Models ICML 2024 Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models ICML 2024 VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models AAAI 2024 BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model ICML 2024 Learning Human-Compatible Representations for Case-Based Decision Support ICLR 2023 Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors IJCAI 2023 On Sparse Modern Hopfield Model NIPS 2023 HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text NIPS 2023 VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models NIPS 2023 Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty AAAI 2023 Boosting Few-Shot Text Classification via Distribution Estimation AAAI 2023 SSPAttack: A Simple and Sweet Paradigm for Black-Box Hard-Label Textual Adversarial Attack AAAI 2023 Aligning Offline Metrics and Human Judgments of Value for Code Generation Models ACL 2023 Feature Programming for Multivariate Time Series Prediction ICML 2023 SlowLiDAR: Increasing the Latency of LiDAR-Based Detection Using Adversarial Examples CVPR 2023 RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural Prompts CVPR 2023 Real-Time Image Demoir$\acute{e}$ing on Mobile Devices ICLR 2023 Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving AAAI 2022 Domain Generalization for Retinal Vessel Segmentation with Vector Field Transformer MIDL 2022 Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory ICLR 2022 Bregman Proximal Langevin Monte Carlo via Bregman-Moreau Envelopes ICML 2022 Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading IJCNLP 2021 Converse, Focus and Guess - Towards Multi-Document Driven Dialogue AAAI 2021 RoboFlow: a Data-centric Workflow Management System for Developing AI-enhanced Robots CORL 2021 Posterior Promoted GAN With Distribution Discriminator for Unsupervised Image Synthesis CVPR 2021 An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling EMNLP 2021 Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading ACL 2021 Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network ACL 2020 Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees ICLR 2020 Agnostic Estimation for Phase Retrieval JMLR 2020 Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification ACL 2020 GLAD: Learning Sparse Graph Recovery ICLR 2020 Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python JMLR 2019 Layer-Wise Learning Strategy for Nonparametric Tensor Product Smoothing Spline Regression and Graphical Models JMLR 2019 Reconstructing Capsule Networks for Zero-shot Intent Classification IJCNLP 2019 Fast Low-rank Metric Learning for Large-scale and High-dimensional Data NIPS 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function UAI 2019 Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications ICLR 2019 Attributed Graph Clustering via Adaptive Graph Convolution IJCAI 2019 Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI ICML 2019 Reconstructing Capsule Networks for Zero-shot Intent Classification EMNLP 2019 Label Efficient Semi-Supervised Learning via Graph Filtering CVPR 2019 On Semiparametric Exponential Family Graphical Models JMLR 2018 Exponentially Weighted Imitation Learning for Batched Historical Data NIPS 2018 Sketching Method for Large Scale Combinatorial Inference NIPS 2018 Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems AISTATS 2018 Feedback-Based Tree Search for Reinforcement Learning ICML 2018 The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference ICML 2018 Graphical Nonconvex Optimization via an Adaptive Convex Relaxation ICML 2018 Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents ICML 2018 Multi-Task Clustering with Model Relation Learning IJCAI 2018 Discrete Factorization Machines for Fast Feature-based Recommendation IJCAI 2018 On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization JMLR 2018 Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models JMLR 2018 Estimating High-dimensional Non-Gaussian Multiple Index Models via Stein’s Lemma NIPS 2017 Diffusion Approximations for Online Principal Component Estimation and Global Convergence NIPS 2017 High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation ICML 2017 CANE: Context-Aware Network Embedding for Relation Modeling ACL 2017 Parametric Simplex Method for Sparse Learning NIPS 2017 Self-Adapted Multi-Task Clustering IJCAI 2016 Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning ICML 2016 On the Statistical Limits of Convex Relaxations ICML 2016 Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes NIPS 2016 More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning NIPS 2016 Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity ICML 2016 An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization AISTATS 2016 A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning AISTATS 2016 Agnostic Estimation for Misspecified Phase Retrieval Models NIPS 2016 Blind Attacks on Machine Learners NIPS 2016 Low-Rank and Sparse Structure Pursuit via Alternating Minimization AISTATS 2016 Non-convex Statistical Optimization for Sparse Tensor Graphical Model NIPS 2015 Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive Processes ICML 2015 Robust Portfolio Optimization NIPS 2015 High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality NIPS 2015 Local Smoothness in Variance Reduced Optimization NIPS 2015 A Direct Estimation of High Dimensional Stationary Vector Autoregressions JMLR 2015 Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery JMLR 2015 Multi-Task Multi-View Clustering for Non-Negative Data IJCAI 2015 The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R JMLR 2015 A Nonconvex Optimization Framework for Low Rank Matrix Estimation NIPS 2015 Optimal Linear Estimation under Unknown Nonlinear Transform NIPS 2015 Accelerated Mini-batch Randomized Block Coordinate Descent Method NIPS 2014 The FASTCLIME Package for Linear Programming and Large-Scale Precision Matrix Estimation in R JMLR 2014 Graph Estimation From Multi-Attribute Data JMLR 2014 Mode Estimation for High Dimensional Discrete Tree Graphical Models NIPS 2014 Sparse PCA with Oracle Property NIPS 2014 Tighten after Relax: Minimax-Optimal Sparse PCA in Polynomial Time NIPS 2014 Multivariate Regression with Calibration NIPS 2014 Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies AISTATS 2014 Sparse Principal Component Analysis for High Dimensional Multivariate Time Series AISTATS 2013 Markov Network Estimation From Multi-attribute Data ICML 2013 Principal Component Analysis on non-Gaussian Dependent Data ICML 2013 Feature Selection in High-Dimensional Classification ICML 2013 Sparse Inverse Covariance Estimation with Calibration NIPS 2013 Transition Matrix Estimation in High Dimensional Time Series ICML 2013 CODA: High Dimensional Copula Discriminant Analysis JMLR 2013 Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model NIPS 2013 Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NIPS 2012 Detecting Network Cliques with Radon Basis Pursuit AISTATS 2012 Marginal Regression For Multitask Learning AISTATS 2012 Sparse Additive Machine AISTATS 2012 Transelliptical Component Analysis NIPS 2012 Exponential Concentration for Mutual Information Estimation with Application to Forests NIPS 2012 Semiparametric Principal Component Analysis NIPS 2012 The huge Package for High-dimensional Undirected Graph Estimation in R JMLR 2012 Transelliptical Graphical Models NIPS 2012 Forest Density Estimation JMLR 2011 The Group Dantzig Selector AISTATS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NIPS 2010 Graph-Valued Regression NIPS 2010 Multivariate Dyadic Regression Trees for Sparse Learning Problems NIPS 2010 Nonparametric Greedy Algorithms for the Sparse Learning Problem NIPS 2009 The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs JMLR 2009 Nonparametric regression and classification with joint sparsity constraints NIPS 2008 SpAM: Sparse Additive Models NIPS 2007