Zhen Fang
32 papers · 2020–2026 · 10 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (52) π Conference Polyglot Β· Gold π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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(11)
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(10)
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(3)
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Venues
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Research topics
Machine Learning
(25)
Artificial Intelligence
(16)
Learning Types Β· Machine Learning
(14)
Application Areas
(13)
Core Methods
(12)
Optimization & Theory
(11)
Core AI
(10)
Deep Learning
(8)
Learning Paradigms
(8)
Learning Types Β· Deep Learning
(5)
Computer Vision
(4)
Models
(3)
Natural Language Processing
(2)
Generation
(2)
Techniques
(2)
Keywords
out-of-distribution detection
(11)
distribution shift
(6)
continual learning
(3)
open-world classification
(2)
vision-language model
(2)
distribution discrepancy
(2)
class imbalance
(2)
pseudo labeling
(2)
representation learning
(2)
feature learning
(2)
generalization bound
(2)
transfer learning
(2)
knowledge distillation
(2)
ood detection
(2)
prompt learning
(2)
catastrophic forgetting
(2)
pac learning
(2)
unsupervised domain adaptation
(2)
semi-supervised learning
(2)
large language model
(2)
Papers
Beyond Accuracy: Unveiling Inefficiency Patterns in Tool-Integrated Reasoning
ACL 2026
UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision
ACL 2026
A Semi-supervised Scalable Unified Framework for E-commerce Query Classification
ACL 2025
CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error Scenarios
EMNLP 2025
Deep Kernel Relative Test for Machine-generated Text Detection
ICLR 2025
NLPrompt: Noise-Label Prompt Learning for Vision-Language Models
CVPR 2025
On the Provable Importance of Gradients for Autonomous Language-Assisted Image Clustering
ICCV 2025
Release the Powers of Prompt Tuning: Cross-Modality Prompt Transfer
ICLR 2025
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
ICML 2025
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
ICLR 2024
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
ICLR 2024
Knowledge Distillation with Auxiliary Variable
ICML 2024
Learning to Shape In-distribution Feature Space for Out-of-distribution Detection
NeurIPS 2024
Negative Label Guided OOD Detection with Pretrained Vision-Language Models
ICLR 2024
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation
ICLR 2024
On the Learnability of Out-of-distribution Detection
JMLR 2024
Out-of-Distribution Detection with Negative Prompts
ICLR 2024
Continual Named Entity Recognition without Catastrophic Forgetting
EMNLP 2023
Detecting Out-of-distribution Data through In-distribution Class Prior
ICML 2023
Invariant Learning via Probability of Sufficient and Necessary Causes
NeurIPS 2023
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection
ICCV 2023
Learning to Augment Distributions for Out-of-distribution Detection
NeurIPS 2023
Meta OOD Learning For Continuously Adaptive OOD Detection
ICCV 2023
Moderately Distributional Exploration for Domain Generalization
ICML 2023
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources
NeurIPS 2023
SODA: Robust Training of Test-Time Data Adaptors
NeurIPS 2023
Federated Class-Incremental Learning
CVPR 2022
Is Out-of-Distribution Detection Learnable?
NeurIPS 2022
Confident Anchor-Induced Multi-Source Free Domain Adaptation
NeurIPS 2021
How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
AAAI 2021
Learning Bounds for Open-Set Learning
ICML 2021
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation
IJCAI 2020