Hao Fang

Orcid: 0009-0004-0271-6579

Affiliations:
  • Tsinghua University, Shenzhen International Graduate School, China


According to our database1, Hao Fang authored at least 36 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Reasoning Matters: Mitigate Hallucination in Multimodal Large Reasoning Models via Reasoning-Conditioned Preference Optimization.
CoRR, May, 2026

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation.
CoRR, May, 2026

Mistletoe: Stealthy Acceleration-Collapse Attacks on Speculative Decoding.
CoRR, May, 2026

Enhancing Gradient Inversion Attacks in Federated Learning via Hierarchical Feature Optimization.
CoRR, April, 2026

Looking Back and Forth: Cross-Image Attention Calibration and Attentive Preference Learning for Multi-Image Hallucination Mitigation.
CoRR, March, 2026

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective.
CoRR, February, 2026

Seeing Through the Chain: Mitigate Hallucination in Multimodal Reasoning Models via CoT Compression and Contrastive Preference Optimization.
CoRR, February, 2026

A temporal-aware generative network for cross-modal video universal adversarial perturbation generation.
Knowl. Based Syst., 2026

Rank Matters: Understanding and Defending Model Inversion Attacks via Low-Rank Feature Filtering.
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

When Efficiency Meets Safety: A Benchmark Security Analysis of KV Cache Compression in Large Language Models.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Retrievals Can Be Detrimental: Unveiling the Backdoor Vulnerability of Retrieval-Augmented Diffusion Models.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025
Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization.
CoRR, August, 2025

Wolf Hidden in Sheep's Conversations: Toward Harmless Data-Based Backdoor Attacks for Jailbreaking Large Language Models.
CoRR, May, 2025

GaussTrap: Stealthy Poisoning Attacks on 3D Gaussian Splatting for Targeted Scene Confusion.
CoRR, April, 2025

Neural Antidote: Class-Wise Prompt Tuning for Purifying Backdoors in Pre-trained Vision-Language Models.
CoRR, February, 2025

Retrievals Can Be Detrimental: A Contrastive Backdoor Attack Paradigm on Retrieval-Augmented Diffusion Models.
CoRR, January, 2025

GI-NAS: Boosting Gradient Inversion Attacks Through Adaptive Neural Architecture Search.
IEEE Trans. Inf. Forensics Secur., 2025

Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

ICAS: Detecting Training Data from Autoregressive Image Generative Models.
Proceedings of the 33rd ACM International Conference on Multimedia, 2025

Stealthy Shield Defense: A Conditional Mutual Information-Based Approach against Black-Box Model Inversion Attacks.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Going Beyond Feature Similarity: Effective Dataset distillation based on Class-aware Conditional Mutual Information.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

One Perturbation is Enough: On Generating Universal Adversarial Perturbations Against Vision-Language Pre-Training Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

RobNAS: Robust Neural Architecture Search for Point Cloud Adversarial Defense.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Your Language Model Can Secretly Write Like Humans: Contrastive Paraphrase Attacks on LLM-Generated Text Detectors.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Hierarchical Features Matter: A Deep Exploration of Progressive Parameterization Method for Dataset Distillation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
CALoR: Towards Comprehensive Model Inversion Defense.
CoRR, 2024

MIBench: A Comprehensive Benchmark for Model Inversion Attack and Defense.
CoRR, 2024

CLIP-Guided Networks for Transferable Targeted Attacks.
CoRR, 2024

Hierarchical Features Matter: A Deep Exploration of GAN Priors for Improved Dataset Distillation.
CoRR, 2024

One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models.
CoRR, 2024

Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses.
CoRR, 2024

FedSMW: Server-Side Model Watermark Framework for Model Ownership Verification in Federated Learning.
Proceedings of the 16th International Conference on Wireless Communications and Signal Processing, 2024

WaterDiff: Perceptual Image Watermarks Via Diffusion Model.
Proceedings of the IEEE International Conference on Acoustics, 2024

A Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion Attacks.
Proceedings of the Computer Vision - ECCV 2024, 2024

CLIP-Guided Generative Networks for Transferable Targeted Adversarial Attacks.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023


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