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20242026
most citedMembership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy

2 citations · 2 across the 16 of their papers we have counts for

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cs.CV2025

NDM: A Noise-driven Detection and Mitigation Framework against Implicit Sexual Intentions in Text-to-Image Generation

Yitong Sun, Yao Huang, Ruochen Zhang +4

Despite the impressive generative capabilities of text-to-image (T2I) diffusion models, they remain vulnerable to generating inappropriate content, especially when confronted with…

cs.LG2025

Diffusion Models as Dataset Distillation Priors

Duo Su, Huyu Wu, Huanran Chen +4

Dataset distillation aims to synthesize compact yet informative datasets from large ones. A significant challenge in this field is achieving a trifecta of diversity, generalization…

cs.LG2025

Reliable Unlearning Harmful Information in LLMs with Metamorphosis Representation Projection

Chengcan Wu, Zeming Wei, Huanran Chen +2

While Large Language Models (LLMs) have demonstrated impressive performance in various domains and tasks, concerns about their safety are becoming increasingly severe. In particula…

cs.CL2025

Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation

Yichi Zhang, Yao Huang, Yifan Wang +10

The trustworthiness of Multimodal Large Language Models (MLLMs) remains an intense concern despite the significant progress in their capabilities. Existing evaluation and mitigatio…

cs.LG2025

Mitigating Overthinking in Large Reasoning Models via Manifold Steering

Yao Huang, Huanran Chen, Shouwei Ruan +3

Recent advances in Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in solving complex tasks such as mathematics and coding. However, these models frequently…

cs.LG2025

Unveiling the Basin-Like Loss Landscape in Large Language Models

Huanran Chen, Yinpeng Dong, Zeming Wei +4

We discover the emergence of \textit{basins} in the loss landscape of large language models. As model scale increases, LLMs become progressively more resilient to random perturbati…

cs.CR2025

Efficient Input-level Backdoor Defense on Text-to-Image Synthesis via Neuron Activation Variation

Shengfang Zhai, Jiajun Li, Yue Liu +7

In recent years, text-to-image (T2I) diffusion models have gained significant attention for their ability to generate high quality images reflecting text prompts. However, their gr…

cs.LG2025

Towards the Worst-case Robustness of Large Language Models

Huanran Chen, Yinpeng Dong, Zeming Wei +2

Recent studies have revealed the vulnerability of large language models to adversarial attacks, where adversaries craft specific input sequences to induce harmful, violent, private…