Jiaqi Lv
16 papers · 2019–2026 · 6 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 (24) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π€ Dynamic Duo (15)
π§¬
Topic Evolution
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(65)
π₯
Unstoppable Β· Bronze
β
The Questioner
π
Conference Pioneer
π
Trend Setter
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(13)
Learning Types Β· Machine Learning
(12)
Core Methods
(11)
Deep Learning
(4)
Learning Types Β· Deep Learning
(3)
Artificial Intelligence
(2)
Core AI
(2)
Computer Science
(1)
Computer Vision
(1)
Analysis
(1)
Applications
(1)
Architectures
(1)
Bayesian & Probabilistic
(1)
Optimization & Theory Β· Deep Learning
(1)
Optimization & Theory Β· Machine Learning
(1)
Keywords
partial label learning
(8)
weakly supervised learning
(4)
label enhancement
(4)
candidate label
(3)
semi-supervised learning
(3)
representation learning
(3)
multi-label learning
(2)
single-positive learning
(2)
label disambiguation
(2)
multi-label classification
(2)
contrastive learning
(2)
multi-class classification
(2)
knowledge transfer
(2)
bayes optimal classifier
(2)
parameter initialization
(2)
label noise
(1)
mutual information
(1)
risk minimization
(1)
variational inference
(1)
image classification
(1)
Papers
A Unified Framework for Knowledge Transfer in Bidirectional Model Scaling
CVPR 2026
ChatHLS: Towards Systematic Design Automation and Optimization for High-Level Synthesis
ACL 2026
Unlocking Pre-trained Weights: Parameter Inheritance for Zero-Shot Initialization
CVPR 2026
Learngene Tells You How to Customize: Task-Aware Parameter Initialization at Flexible Scales
ICML 2025
Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency
ICML 2024
What Makes Partial-Label Learning Algorithms Effective?
NeurIPS 2024
FREDIS: A Fusion Framework of Refinement and Disambiguation for Unreliable Partial Label Learning
ICML 2023
Progressive Purification for Instance-Dependent Partial Label Learning
ICML 2023
Revisiting Pseudo-Label for Single-Positive Multi-Label Learning
ICML 2023
Towards Effective Visual Representations for Partial-Label Learning
CVPR 2023
Ambiguity-Induced Contrastive Learning for Instance-Dependent Partial Label Learning
IJCAI 2022
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement
NeurIPS 2022
Progressive Identification of True Labels for Partial-Label Learning
ICML 2020
Provably Consistent Partial-Label Learning
NeurIPS 2020
Partial Label Learning via Label Enhancement
AAAI 2019
Weakly Supervised Multi-Label Learning via Label Enhancement
IJCAI 2019