Xingchao Liu
23 papers · 2020–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (5) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (8) π Cross-Pollinator (10)
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Cross-Pollinator
(10)
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Renaissance Researcher
(8)
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Taxonomy Completionist
(39)
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Grand Slam
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Dynamic Duo
(17)
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Topic Evolution
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Keyword Collector
(86)
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Century Club
(23)
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Unstoppable
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Prolific Year
(5)
Conferences
NIPS (9)
CVPR (4)
ICLR (3)
AAAI (2)
NAACL (2)
ECCV (1)
EMNLP (1)
ICML (1)
Top co-authors
Keywords
diffusion model
(5)
image generation
(3)
knowledge distillation
(2)
vision-language model
(2)
ordinary differential equation
(2)
neural network optimization
(2)
markov chain monte carlo
(2)
flow matching
(2)
autoregressive model
(2)
gradient-based sampling
(2)
multimodal understanding
(2)
rectified flow
(2)
point cloud generation
(2)
multimodal learning
(2)
model compression
(2)
knowledge transfer
(1)
image classification
(1)
imitation learning
(1)
probabilistic modeling
(1)
langevin dynamics
(1)
Papers
JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation
CVPR 2025
Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation
CVPR 2025
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
ICLR 2024
SlimFlow: Training Smaller One-Step Diffusion Models with Rectified Flow
ECCV 2024
LanguageFlow: Advancing Diffusion Language Generation with Probabilistic Flows
NAACL 2024
AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies
NIPS 2024
PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator
NIPS 2024
Layer Compression of Deep Networks with Straight Flows
AAAI 2024
Fast Point Cloud Generation With Straight Flows
CVPR 2023
DISCS: A Benchmark for Discrete Sampling
NIPS 2023
FlowGrad: Controlling the Output of Generative ODEs With Gradients
CVPR 2023
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
ICLR 2023
Learning Diffusion Bridges on Constrained Domains
ICLR 2023
Diffusion-based Molecule Generation with Informative Prior Bridges
NIPS 2022
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models
EMNLP 2022
ALLSH: Active Learning Guided by Local Sensitivity and Hardness
NAACL 2022
A Langevin-like Sampler for Discrete Distributions
ICML 2022
Profiling Pareto Front With Multi-Objective Stein Variational Gradient Descent
NIPS 2021
Conflict-Averse Gradient Descent for Multi-task learning
NIPS 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
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision
AAAI 2021
Certified Monotonic Neural Networks
NIPS 2020