2025
NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction.
CoRR, June, 2025
Sparsification and Reconstruction from the Perspective of Representation Geometry.
CoRR, May, 2025
Learning With Noisy Labels Over Imbalanced Subpopulations.
IEEE Trans. Neural Networks Learn. Syst., April, 2025
Measuring Diversity in Synthetic Datasets.
CoRR, February, 2025
A Review and Experimental Evaluation on Split Learning.
Future Internet, 2025
Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection.
ACM Trans. Knowl. Discov. Data, September, 2024
Probing the Safety Response Boundary of Large Language Models via Unsafe Decoding Path Generation.
CoRR, 2024
RiskAwareBench: Towards Evaluating Physical Risk Awareness for High-level Planning of LLM-based Embodied Agents.
CoRR, 2024
Invariant Test-Time Adaptation for Vision-Language Model Generalization.
CoRR, 2024
LLM Inference Unveiled: Survey and Roofline Model Insights.
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CoRR, 2024
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping.
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CoRR, 2024
Rethinking and Simplifying Bootstrapped Graph Latents.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024
Rethinking the Reliability of Post-hoc Calibration Methods Under Subpopulation Shift.
Proceedings of the PRICAI 2024: Trends in Artificial Intelligence, 2024
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
A Label Disambiguation-Based Multimodal Massive Multiple Instance Learning Approach for Immune Repertoire Classification.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
COPPER: a combinatorial optimization problem solver with processing-in-memory architecture.
Frontiers Inf. Technol. Electron. Eng., May, 2023
Lightweight Privacy-Preserving Federated Incremental Decision Trees.
IEEE Trans. Serv. Comput., 2023
Dynamics Adapted Imitation Learning.
Trans. Mach. Learn. Res., 2023
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy.
CoRR, 2023
Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale.
CoRR, 2023
Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning.
CoRR, 2023
VDC: Versatile Data Cleanser for Detecting Dirty Samples via Visual-Linguistic Inconsistency.
CoRR, 2023
Semantic Equivariant Mixup.
CoRR, 2023
Uncertainty in Natural Language Processing: Sources, Quantification, and Applications.
CoRR, 2023
Attention Paper: How Generative AI Reshapes Digital Shadow Industry?
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CoRR, 2023
Reweighted Mixup for Subpopulation Shift.
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CoRR, 2023
SLPerf: a Unified Framework for Benchmarking Split Learning.
CoRR, 2023
RPTQ: Reorder-based Post-training Quantization for Large Language Models.
CoRR, 2023
Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance.
CoRR, 2023
Fairness-guided Few-shot Prompting for Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
IIB-MIL: Integrated Instance-Level and Bag-Level Multiple Instances Learning with Label Disambiguation for Pathological Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Calibrating Multimodal Learning.
Proceedings of the International Conference on Machine Learning, 2023
Federated Nearest Neighbor Machine Translation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.
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Proceedings of the Eleventh International Conference on Learning Representations, 2023
PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Density-Aware Prototypical Network for Few-Shot Relation Classification.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Post-Training Quantization on Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
SAILOR: Structural Augmentation Based Tail Node Representation Learning.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Attention Paper: How Generative AI Reshapes Digital Shadow Industry?
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Proceedings of the ACM Turing Award Celebration Conference - China 2023, 2023
E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations.
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Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design.
ACM Trans. Intell. Syst. Technol., 2022
Learning with Noisy Labels over Imbalanced Subpopulations.
CoRR, 2022
Vertical Federated Linear Contextual Bandits.
CoRR, 2022
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery.
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CoRR, 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.
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CoRR, 2022
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup.
CoRR, 2022
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift.
CoRR, 2022
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations.
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CoRR, 2022
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network.
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Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2022
2021
ASFGNN: Automated separated-federated graph neural network.
Peer-to-Peer Netw. Appl., 2021
Generalization Bounds for Stochastic Gradient Langevin Dynamics: A Unified View via Information Leakage Analysis.
CoRR, 2021
NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators.
Sci. China Inf. Sci., 2021
HASCO: Towards Agile HArdware and Software CO-design for Tensor Computation.
Proceedings of the 48th ACM/IEEE Annual International Symposium on Computer Architecture, 2021
2020
Practical Privacy Preserving POI Recommendation.
ACM Trans. Intell. Syst. Technol., 2020
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design.
CoRR, 2020
S3ML: A Secure Serving System for Machine Learning Inference.
CoRR, 2020
ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference.
CoRR, 2020
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning.
CoRR, 2020
Privacy-Preserving Graph Neural Network for Node Classification.
CoRR, 2020
Industrial Scale Privacy Preserving Deep Neural Network.
CoRR, 2020
Practical Privacy Preserving POI Recommendation.
CoRR, 2020
Automatic Knowledge Fusion in Transferrable Networks for Semantic Text Matching.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020
SaFace: Towards Scenario-aware Face Recognition via Edge Computing System.
Proceedings of the 3rd USENIX Workshop on Hot Topics in Edge Computing, 2020
S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search.
Proceedings of the Computer Vision - ECCV 2020, 2020
Secure Social Recommendation Based on Secret Sharing.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020
Nebula: A Scalable Privacy-Preserving Machine Learning System in Ant Financial.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
P3SGD: Patient Privacy Preserving SGD for Regularizing Deep CNNs in Pathological Image Classification.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2017
SRPGAN: Perceptual Generative Adversarial Network for Single Image Super Resolution.
CoRR, 2017
Reducing Overfitting in Deep Convolutional Neural Networks Using Redundancy Regularizer.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017