← Authors

Qiang Liu

174 papers · 2010–2026 · 15 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌍 Conference Polyglot (15) πŸ—ΊοΈ Taxonomy Completionist (48) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (15) 🌈 Renaissance Researcher (9) πŸŒ‰ Interdisciplinary Bridge 🏠 Conference Loyalist (50) 🌟 Keyword Trendsetter Combo (9) 🀝 Dynamic Duo (29) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam 🌱 Topic Pioneer πŸ”¬ Deep Specialist (33) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (16) ⚑ Prolific Year (18) πŸ’Ž Century Club (173) πŸ—ƒοΈ Keyword Collector (152) ❓ The Questioner (2)

Conferences

NIPS (50) ICML (27) ICLR (22) ACL (15) CVPR (13) EMNLP (12) AAAI (11) AISTATS (7) IJCAI (5) ICCV (3) UAI (3) ECCV (2) JMLR (2) ACML (1) NAACL (1)

Top co-authors

Shu Wu (29) Liang Wang (29) Chengyue Gong (21) Jian Peng (18) Mao Ye (18) Xingchao Liu (17) Dilin Wang (16) Bo Liu (16) Lemeng Wu (13) Alex Ihler (8)

Research topics

Statistics (1)

Keywords

variational inference (15) stein variational gradient descent (10) large language model (10) diffusion model (10) model compression (9) neural network (8) gradient descent (8) multimodal learning (7) graphical model (7) attention mechanism (6) image classification (5) generative model (5) kl divergence (5) neural network optimization (5) reinforcement learning (5) kernel methods (5) graph neural network (5) importance sampling (4) discrete distribution (4) image generation (4)

Papers

Q Cache: Visual Attention Is Valuable in Less than Half of Decode Layers for Multimodal Large Language Model AAAI 2026
PIPA: Preference Alignment as Prior-Informed Statistical Estimation ICML 2025
PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations ICML 2025
SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization ICML 2025
ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks ICLR 2025
Longhorn: State Space Models are Amortized Online Learners ICLR 2025
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra ICLR 2025
Uncovering Overfitting in Large Language Model Editing ICLR 2025
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows ICLR 2025
PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations ICLR 2025
LIRA: Inferring Segmentation in Large Multi-modal Models with Local Interleaved Region Assistance ICCV 2025
Improving Rectified Flow with Boundary Conditions ICCV 2025
KELE: Residual Knowledge Erasure for Enhanced Multi-hop Reasoning in Knowledge Editing EMNLP 2025
GenPilot: A Multi-Agent System for Test-Time Prompt Optimization in Image Generation EMNLP 2025
Toolscaler: Scalable Generative Tool Calling via Structure-Aware Semantic Tokenization EMNLP 2025
Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models EMNLP 2025
REACT: Representation Extraction And Controllable Tuning to Overcome Overfitting in LLM Knowledge Editing EMNLP 2025
SHARP: Steering Hallucination in LVLMs via Representation Engineering EMNLP 2025
Steepest Descent Density Control for Compact 3D Gaussian Splatting CVPR 2025
InsightEdit: Towards Better Instruction Following for Image Editing CVPR 2025
AMO Sampler: Enhancing Text Rendering with Overshooting CVPR 2025
SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity AISTATS 2025
Memory-Efficient Optimization with Factorized Hamiltonian Descent AISTATS 2025
A2ATS: Retrieval-Based KV Cache Reduction via Windowed Rotary Position Embedding and Query-Aware Vector Quantization ACL 2025
VidCapBench: A Comprehensive Benchmark of Video Captioning for Controllable Text-to-Video Generation ACL 2025
Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models ACL 2025
Generate First, Then Sample: Enhancing Fake News Detection with LLM-Augmented Reinforced Sampling ACL 2025
SINCon: Mitigate LLM-Generated Malicious Message Injection Attack for Rumor Detection ACL 2025
Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG ACL 2025
Personalized Text Generation with Contrastive Activation Steering ACL 2025
ST3: Accelerating Multimodal Large Language Model by Spatial-Temporal Visual Token Trimming AAAI 2025
CoRA: Collaborative Information Perception by Large Language Model’s Weights for Recommendation AAAI 2025
EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification ACL 2024
VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark NIPS 2024
Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization NIPS 2024
Communication Efficient Distributed Training with Distributed Lion NIPS 2024
Quadratic Quantum Variational Monte Carlo NIPS 2024
Enhancing Protein Mutation Effect Prediction through a Retrieval-Augmented Framework NIPS 2024
Memory-Efficient LLM Training with Online Subspace Descent NIPS 2024
Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction NIPS 2024
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator NIPS 2024
AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies NIPS 2024
Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables AAAI 2024
Text-Guided Molecule Generation with Diffusion Language Model AAAI 2024
Layer Compression of Deep Networks with Straight Flows AAAI 2024
Rethinking Graph Masked Autoencoders through Alignment and Uniformity AAAI 2024
Stealthy Attack on Large Language Model based Recommendation ACL 2024
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models ACL 2024
Chain-of-History Reasoning for Temporal Knowledge Graph Forecasting ACL 2024
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models CVPR 2024
Taming Mode Collapse in Score Distillation for Text-to-3D Generation CVPR 2024
Solving Motion Planning Tasks with a Scalable Generative Model ECCV 2024
SlimFlow: Training Smaller One-Step Diffusion Models with Rectified Flow ECCV 2024
Knowledge Graph Enhanced Large Language Model Editing EMNLP 2024
Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts ICLR 2024
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation ICLR 2024
Evolution-Inspired Loss Functions for Protein Representation Learning ICML 2024
A Computational Framework for Solving Wasserstein Lagrangian Flows ICML 2024
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames ICML 2024
Image as a Foreign Language: BEiT Pretraining for Vision and Vision-Language Tasks CVPR 2023
Sparsely Annotated Semantic Segmentation With Adaptive Gaussian Mixtures CVPR 2023
Fast Point Cloud Generation With Straight Flows CVPR 2023
Counterfactual Debiasing for Fact Verification ACL 2023
Learning Latent Relations for Temporal Knowledge Graph Reasoning ACL 2023
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design ICML 2023
Language Is Not All You Need: Aligning Perception with Language Models NIPS 2023
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body SchrΓΆdinger Equation NIPS 2023
FAMO: Fast Adaptive Multitask Optimization NIPS 2023
Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning AAAI 2023
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning NIPS 2023
GSLB: The Graph Structure Learning Benchmark NIPS 2023
Uncovering Neural Scaling Laws in Molecular Representation Learning NIPS 2023
Learning Diffusion Bridges on Constrained Domains ICLR 2023
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow ICLR 2023
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing ICLR 2023
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation ICML 2023
Sampling with Mollified Interaction Energy Descent ICLR 2023
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting ICCV 2023
Noise-Robust Semi-Supervised Learning for Distantly Supervised Relation Extraction EMNLP 2023
DUBLIN: Visual Document Understanding By Language-Image Network EMNLP 2023
FlowGrad: Controlling the Output of Generative ODEs With Gradients CVPR 2023
Planning-Oriented Autonomous Driving CVPR 2023
First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data NIPS 2022
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach NIPS 2022
Bootstrapping a high quality multilingual multimodal dataset for Bletchley ACML 2022
GraphDIVE: Graph Classification by Mixture of Diverse Experts IJCAI 2022
Attention and Edge-Label Guided Graph Convolutional Networks for Named Entity Recognition EMNLP 2022
MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning EMNLP 2022
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training ICLR 2022
Energy-Inspired Molecular Conformation Optimization ICLR 2022
Harmless Transfer Learning for Item Embeddings NAACL 2022
Diffusion-based Molecule Generation with Informative Prior Bridges NIPS 2022
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent NIPS 2022
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity ICML 2022
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference ICML 2022
A Langevin-like Sampler for Discrete Distributions ICML 2022
Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set UAI 2022
AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Clouds AAAI 2022
Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems UAI 2022
VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts NIPS 2022
Conflict-Averse Gradient Descent for Multi-task learning NIPS 2021
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision AAAI 2021
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach NIPS 2021
Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds ICLR 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments ICLR 2021
AlphaMatch: Improving Consistency for Semi-Supervised Learning With Alpha-Divergence CVPR 2021
KeepAugment: A Simple Information-Preserving Data Augmentation Approach CVPR 2021
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training CVPR 2021
Sampling with Trusthworthy Constraints: A Variational Gradient Framework NIPS 2021
argmax centroid NIPS 2021
Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent NIPS 2021
AlphaNet: Improved Training of Supernets with Alpha-Divergence ICML 2021
A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family JMLR 2021
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition ICML 2021
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions ACL 2020
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks NIPS 2020
An efficient representation of chronological events in medical texts EMNLP 2020
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection ICML 2020
A Chance-Constrained Generative Framework for Sequence Optimization ICML 2020
Accountable Off-Policy Evaluation With Kernel Bellman Statistics ICML 2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples NIPS 2020
Implicit Regularization and Convergence for Weight Normalization NIPS 2020
Off-Policy Interval Estimation with Lipschitz Value Iteration NIPS 2020
Stein Variational Inference for Discrete Distributions AISTATS 2020
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough NIPS 2020
Certified Monotonic Neural Networks NIPS 2020
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks ICML 2020
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework NIPS 2020
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning ICLR 2020
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation ICLR 2020
Splitting Steepest Descent for Growing Neural Architectures NIPS 2019
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel NIPS 2019
Stein Variational Gradient Descent With Matrix-Valued Kernels NIPS 2019
Exploration via Hindsight Goal Generation NIPS 2019
A Kernel Loss for Solving the Bellman Equation NIPS 2019
Learning Self-Imitating Diverse Policies ICLR 2019
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy ICLR 2019
Learning Belief Representations for Imitation Learning in POMDPs UAI 2019
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization ICML 2019
Improving Neural Language Modeling via Adversarial Training ICML 2019
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models ICML 2019
Robustness Can Be Cheap: A Highly Efficient Approach to Discover Outliers under High Outlier Ratios AAAI 2019
Variational Inference with Tail-adaptive f-Divergence NIPS 2018
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation NIPS 2018
Learning to Explore via Meta-Policy Gradient ICML 2018
Stein Variational Message Passing for Continuous Graphical Models ICML 2018
Multi-agent Epistemic Planning with Common Knowledge IJCAI 2018
Stein Variational Gradient Descent Without Gradient ICML 2018
Stein Variational Gradient Descent as Moment Matching NIPS 2018
Efficient Localized Inference for Large Graphical Models IJCAI 2018
Energy-efficient Amortized Inference with Cascaded Deep Classifiers IJCAI 2018
On the Discrimination-Generalization Tradeoff in GANs ICLR 2018
Action-dependent Control Variates for Policy Optimization via Stein Identity ICLR 2018
Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy ICML 2018
Black-box Importance Sampling AISTATS 2017
Stein Variational Gradient Descent as Gradient Flow NIPS 2017
Local Perturb-and-MAP for Structured Prediction AISTATS 2017
A Convolutional Approach for Misinformation Identification IJCAI 2017
Communication-efficient Sparse Regression JMLR 2017
A Kernelized Stein Discrepancy for Goodness-of-fit Tests ICML 2016
Learning Infinite RBMs with Frank-Wolfe NIPS 2016
Bootstrap Model Aggregation for Distributed Statistical Learning NIPS 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NIPS 2016
Probabilistic Variational Bounds for Graphical Models NIPS 2015
Decomposition Bounds for Marginal MAP NIPS 2015
Distributed Estimation, Information Loss and Exponential Families NIPS 2014
Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy ICML 2014
Marginal Structured SVM with Hidden Variables ICML 2014
Variational Planning for Graph-based MDPs NIPS 2013
Scoring Workers in Crowdsourcing: How Many Control Questions are Enough? NIPS 2013
Variational Inference for Crowdsourcing NIPS 2012
Computational Approaches to Sentence Completion ACL 2012
Learning Scale Free Networks by Reweighted $\ell_1$ regularization AISTATS 2011
Learning with Blocks: Composite Likelihood and Contrastive Divergence AISTATS 2010