Qiang Liu
176 papers · 2010–2026 · 15 conferences · across top CS/AI conferences
Achievements
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Conferences
NIPS (50)
ICML (27)
ICLR (22)
ACL (17)
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
Research topics
Keywords
variational inference
(15)
diffusion model
(10)
stein variational gradient descent
(10)
large language model
(10)
model compression
(9)
gradient descent
(8)
neural network
(8)
multimodal learning
(7)
graphical model
(7)
attention mechanism
(6)
graph neural network
(5)
image classification
(5)
generative model
(5)
kl divergence
(5)
neural network optimization
(5)
kernel methods
(5)
vision-language model
(5)
reinforcement learning
(5)
importance sampling
(4)
discrete distribution
(4)
Papers
RealChart2Code: Bridging the Gap in Real-World Chart-to-Code Generation via Multi-Task Evaluation
ACL 2026
Q Cache: Visual Attention Is Valuable in Less than Half of Decode Layers for Multimodal Large Language Model
AAAI 2026
From Completion to Editing: Unlocking Context-Aware Code Infilling via Search-and-Replace Instruction Tuning
ACL 2026
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
ICLR 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
Generate First, Then Sample: Enhancing Fake News Detection with LLM-Augmented Reinforced Sampling
ACL 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
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
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
ST3: Accelerating Multimodal Large Language Model by Spatial-Temporal Visual Token Trimming
AAAI 2025
CoRA: Collaborative Information Perception by Large Language Modelβs Weights for Recommendation
AAAI 2025
Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models
ACL 2025
Personalized Text Generation with Contrastive Activation Steering
ACL 2025
Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG
ACL 2025
SINCon: Mitigate LLM-Generated Malicious Message Injection Attack for Rumor Detection
ACL 2025
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models
ACL 2024
EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification
ACL 2024
Chain-of-History Reasoning for Temporal Knowledge Graph Forecasting
ACL 2024
Text-Guided Molecule Generation with Diffusion Language Model
AAAI 2024
Taming Mode Collapse in Score Distillation for Text-to-3D Generation
CVPR 2024
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal Models
CVPR 2024
Layer Compression of Deep Networks with Straight Flows
AAAI 2024
Stealthy Attack on Large Language Model based Recommendation
ACL 2024
Evolution-Inspired Loss Functions for Protein Representation Learning
ICML 2024
A Computational Framework for Solving Wasserstein Lagrangian Flows
ICML 2024
Rethinking Graph Masked Autoencoders through Alignment and Uniformity
AAAI 2024
FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames
ICML 2024
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
ICLR 2024
Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts
ICLR 2024
Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables
AAAI 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
Knowledge Graph Enhanced Large Language Model Editing
EMNLP 2024
SlimFlow: Training Smaller One-Step Diffusion Models with Rectified Flow
ECCV 2024
Solving Motion Planning Tasks with a Scalable Generative Model
ECCV 2024
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator
NIPS 2024
AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies
NIPS 2024
Efficient Transformer-based 3D Object Detection with Dynamic Token Halting
ICCV 2023
Uncovering Neural Scaling Laws in Molecular Representation Learning
NIPS 2023
GSLB: The Graph Structure Learning Benchmark
NIPS 2023
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
NIPS 2023
FAMO: Fast Adaptive Multitask Optimization
NIPS 2023
Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body SchrΓΆdinger Equation
NIPS 2023
Language Is Not All You Need: Aligning Perception with Language Models
NIPS 2023
Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning
AAAI 2023
Counterfactual Debiasing for Fact Verification
ACL 2023
Learning Latent Relations for Temporal Knowledge Graph Reasoning
ACL 2023
Fast Point Cloud Generation With Straight Flows
CVPR 2023
Sparsely Annotated Semantic Segmentation With Adaptive Gaussian Mixtures
CVPR 2023
Image as a Foreign Language: BEiT Pretraining for Vision and Vision-Language Tasks
CVPR 2023
Planning-Oriented Autonomous Driving
CVPR 2023
FlowGrad: Controlling the Output of Generative ODEs With Gradients
CVPR 2023
DUBLIN: Visual Document Understanding By Language-Image Network
EMNLP 2023
Noise-Robust Semi-Supervised Learning for Distantly Supervised Relation Extraction
EMNLP 2023
Sampling with Mollified Interaction Energy Descent
ICLR 2023
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing
ICLR 2023
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
ICLR 2023
Learning Diffusion Bridges on Constrained Domains
ICLR 2023
DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design
ICML 2023
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
ICML 2023
Harmless Transfer Learning for Item Embeddings
NAACL 2022
A Langevin-like Sampler for Discrete Distributions
ICML 2022
Diffusion-based Molecule Generation with Informative Prior Bridges
NIPS 2022
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity
ICML 2022
Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems
UAI 2022
Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set
UAI 2022
Energy-Inspired Molecular Conformation Optimization
ICLR 2022
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training
ICLR 2022
VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts
NIPS 2022
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
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent
NIPS 2022
Bootstrapping a high quality multilingual multimodal
dataset for Bletchley
ACML 2022
AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Clouds
AAAI 2022
Centroid Approximation for Bootstrap: Improving Particle Quality at Inference
ICML 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
GraphDIVE: Graph Classification by Mixture of Diverse Experts
IJCAI 2022
AlphaMatch: Improving Consistency for Semi-Supervised Learning With Alpha-Divergence
CVPR 2021
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training
CVPR 2021
Automatic and Harmless Regularization with Constrained and Lexicographic Optimization: A Dynamic Barrier Approach
NIPS 2021
Sampling with Trusthworthy Constraints: A Variational Gradient Framework
NIPS 2021
Conflict-Averse Gradient Descent for Multi-task learning
NIPS 2021
A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family
JMLR 2021
Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent
NIPS 2021
argmax centroid
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
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition
ICML 2021
AlphaNet: Improved Training of Supernets with Alpha-Divergence
ICML 2021
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision
AAAI 2021
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
CVPR 2021
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning
ICLR 2020
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation
ICLR 2020
Certified Monotonic Neural Networks
NIPS 2020
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions
ACL 2020
An efficient representation of chronological events in medical texts
EMNLP 2020
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks
NIPS 2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples
NIPS 2020
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough
NIPS 2020
Implicit Regularization and Convergence for Weight Normalization
NIPS 2020
Off-Policy Interval Estimation with Lipschitz Value Iteration
NIPS 2020
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework
NIPS 2020
Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
ICML 2020
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
ICML 2020
Stein Variational Inference for Discrete Distributions
AISTATS 2020
Accountable Off-Policy Evaluation With Kernel Bellman Statistics
ICML 2020
A Chance-Constrained Generative Framework for Sequence Optimization
ICML 2020
Improving Neural Language Modeling via Adversarial Training
ICML 2019
Robustness Can Be Cheap: A Highly Efficient Approach to Discover Outliers under High Outlier Ratios
AAAI 2019
Learning Belief Representations for Imitation Learning in POMDPs
UAI 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
Splitting Steepest Descent for Growing Neural Architectures
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
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization
ICML 2019
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models
ICML 2019
Stein Variational Message Passing for Continuous Graphical Models
ICML 2018
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
NIPS 2018
Variational Inference with Tail-adaptive f-Divergence
NIPS 2018
Stein Variational Gradient Descent as Moment Matching
NIPS 2018
Stein Variational Gradient Descent Without Gradient
ICML 2018
Learning to Explore via Meta-Policy Gradient
ICML 2018
Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy
ICML 2018
Efficient Localized Inference for Large Graphical Models
IJCAI 2018
Multi-agent Epistemic Planning with Common Knowledge
IJCAI 2018
Energy-efficient Amortized Inference with Cascaded Deep Classifiers
IJCAI 2018
Action-dependent Control Variates for Policy Optimization via Stein Identity
ICLR 2018
On the Discrimination-Generalization Tradeoff in GANs
ICLR 2018
Stein Variational Gradient Descent as Gradient Flow
NIPS 2017
A Convolutional Approach for Misinformation Identification
IJCAI 2017
Black-box Importance Sampling
AISTATS 2017
Local Perturb-and-MAP for Structured Prediction
AISTATS 2017
Communication-efficient Sparse Regression
JMLR 2017
A Kernelized Stein Discrepancy for Goodness-of-fit Tests
ICML 2016
Bootstrap Model Aggregation for Distributed Statistical Learning
NIPS 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
NIPS 2016
Learning Infinite RBMs with Frank-Wolfe
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
Computational Approaches to Sentence Completion
ACL 2012
Variational Inference for Crowdsourcing
NIPS 2012
Learning Scale Free Networks by Reweighted $\ell_1$ regularization
AISTATS 2011
Learning with Blocks: Composite Likelihood and Contrastive Divergence
AISTATS 2010