← Authors

Bingzhe Wu

26 papers · 2019–2025 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (52) 🌱 Topic Pioneer πŸ† Grand Slam πŸ† Keyword Champion (2) πŸ‘‘ Triple Crown πŸ—ƒοΈ Keyword Collector (98) ⚑ Prolific Year (11) πŸš€ Conference Pioneer πŸ’Ž Century Club (26)

Conferences

AAAI (5) ICML (5) EMNLP (4) ICLR (3) NIPS (3) CVPR (2) IJCAI (2) ACL (1) ECCV (1)

Top co-authors

Yatao Bian (7) Peilin Zhao (7) Guangyu Sun (6) Shiwan Zhao (6) Liang Chen (5) Xiaolu Zhang (4) Changqing Zhang (4) Chaochao Chen (3) Qichao Wang (3) Zhirui Zhang (3)

Research topics

Differential Privacy (2) Privacy (1)

Keywords

uncertainty quantification (3) graph neural network (3) domain generalization (3) differential privacy (3) confidence calibration (2) few-shot learning (2) large language model (2) model robustness (2) membership attack (2) multimodal learning (2) predictive confidence (2) secure computation (1) stochastic gradient descent (1) density estimation (1) domain adaptation (1) privacy attack (1) federated learning (1) named entity recognition (1) post-training quantization (1) chain-of-thought reasoning (1)

Papers

NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction ICML 2025
IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck ICML 2025
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model AAAI 2025
Measuring Diversity in Synthetic Datasets ICML 2025
VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models ICLR 2024
A Label Disambiguation-Based Multimodal Massive Multiple Instance Learning Approach for Immune Repertoire Classification AAAI 2024
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform ICML 2024
Fairness-guided Few-shot Prompting for Large Language Models NIPS 2023
E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition ACL 2023
Calibrating Multimodal Learning ICML 2023
Post-Training Quantization on Diffusion Models CVPR 2023
Federated Nearest Neighbor Machine Translation ICLR 2023
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators EMNLP 2023
Density-Aware Prototypical Network for Few-Shot Relation Classification EMNLP 2023
PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection EMNLP 2023
RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data EMNLP 2023
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations AAAI 2023
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization ICLR 2023
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification IJCAI 2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup NIPS 2022
S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search ECCV 2020
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics AAAI 2020
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification CVPR 2019
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification AAAI 2019
BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference IJCAI 2019
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection NIPS 2019