Yue Ding
11 papers · 2017–2026 · 8 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.
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Research topics
Deep Learning
(7)
Machine Learning
(7)
Artificial Intelligence
(5)
Optimization & Theory
(5)
Core AI
(4)
Architectures
(3)
Models
(3)
Computer Vision
(2)
Natural Language Processing
(2)
Application Areas
(2)
Core Methods
(2)
Learning Types
(2)
Resources & Methods
(2)
Healthcare & Medicine
(1)
Reinforcement Learning
(1)
Keywords
recommender system
(2)
hallucination detection
(2)
convolutional neural network
(2)
reinforcement learning
(1)
multi-task learning
(1)
image generation
(1)
zero-shot learning
(1)
transductive learning
(1)
collaborative filtering
(1)
attention mechanism
(1)
visual reasoning
(1)
visual grounding
(1)
model merging
(1)
model aggregation
(1)
contextual representation
(1)
deep learning
(1)
message passing
(1)
generalization ability
(1)
stacked denoising autoencoder
(1)
embedding space
(1)
Papers
Dejavu: Towards Experience Feedback Learning for Embodied Intelligence
CVPR 2026
RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark
CVPR 2026
Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models
EMNLP 2025
BECAME: Bayesian Continual Learning with Adaptive Model Merging
ICML 2025
Discretized Gaussian Representation for Tomographic Reconstruction
ICCV 2025
SHARP: Steering Hallucination in LVLMs via Representation Engineering
EMNLP 2025
FedHCA2: Towards Hetero-Client Federated Multi-Task Learning
CVPR 2024
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes
ICLR 2024
On Isotropy Calibration of Transformer Models
ACL 2022
CFM: Convolutional Factorization Machines for Context-Aware Recommendation
IJCAI 2019
PHD: A Probabilistic Model of Hybrid Deep Collaborative Filtering for Recommender Systems
ACML 2017