Bin Shi
16 papers · 2019–2026 · 7 venues · across top CS/AI venues
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🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (43) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint
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Dynamic Duo
(10)
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(7)
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Prolific Year · Productive
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Century Club · Bronze
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Research topics
Machine Learning
(11)
Artificial Intelligence
(7)
Deep Learning
(7)
Core AI
(6)
Learning Types · Machine Learning
(6)
Optimization & Theory · Machine Learning
(6)
Mathematics & Optimization
(4)
Core Methods
(4)
Learning Types · Deep Learning
(4)
Optimization
(4)
Natural Language Processing
(3)
Architectures
(2)
Optimization & Theory · Deep Learning
(2)
Understanding
(2)
Computer Vision
(1)
Keywords
multimodal learning
(2)
large language model
(2)
graph neural network
(2)
stochastic gradient descent
(2)
stochastic differential equation
(2)
accelerated gradient method
(2)
convergence rate
(2)
non-convex optimization
(1)
few-shot learning
(1)
reinforcement learning
(1)
hyperparameter optimization
(1)
uncertainty quantification
(1)
noisy label learning
(1)
named entity recognition
(1)
sequence labeling
(1)
anomaly detection
(1)
zero-shot learning
(1)
out-of-distribution generalization
(1)
numerical optimization
(1)
deep learning
(1)
Papers
Enhancing Pre-training Data Detection in LLMs Through Discriminative and Symmetric Prefix Selection
AAAI 2026
Mitigating Instance Entanglement in Instance-Dependent Partial Label Learning
CVPR 2026
Scope Delineation Before Localization: A Two-Stage Framework for Enhancing Failure Attribution in Multi-Agent Systems
AAAI 2026
AHVE-CNER: Aligned Hanzi Visual Encoding Enhance Chinese Named Entity Recognition with Multi-Information
COLING 2025
Out-of-Distribution Generalization on Graphs via Progressive Inference
AAAI 2025
Quantum Optimization via Gradient-Based Hamiltonian Descent
ICML 2025
Revisiting Graph Contrastive Learning on Anomaly Detection: A Structural Imbalance Perspective
AAAI 2025
VERO: Verification and Zero-Shot Feedback Acquisition for Few-Shot Multimodal Aspect-Level Sentiment Classification
AAAI 2025
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label Learning
CVPR 2024
On the Hyperparameters in Stochastic Gradient Descent with Momentum
JMLR 2024
RR-PU: A Synergistic Two-Stage Positive and Unlabeled Learning Framework for Robust Tax Evasion Detection
AAAI 2024
The Evidence Contraction Issue in Deep Evidential Regression: Discussion and Solution
AAAI 2024
NerCo: A Contrastive Learning Based Two-Stage Chinese NER Method
IJCAI 2023
On Learning Rates and Schrödinger Operators
JMLR 2023
Reinforcement Learning Approaches for Traffic Signal Control under Missing Data
IJCAI 2023
Acceleration via Symplectic Discretization of High-Resolution Differential Equations
NeurIPS 2019