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Kunhao Li

2 accepted papers

2026

Cross-Modal Unlearning via Influential Neuron Path Editing in Multimodal Large Language Models

AAAI 2026technical

Multimodal Large Language Models (MLLMs) extend foundation models to real-world applications by integrating inputs such as text and vision. However, their broad knowledge capacity raises growing concerns about privacy leakage, toxicity mitigation, and intellectual property violations. Machine Unlear

Cited by 0SourcePDFScholar
2026

HiddenEcho: Mitigating Noise Amplification in Differentially Private LLMs with Hidden-State Correction

ICLR 2026poster

The rise of large language models (LLMs) has driven the adoption of Model-as-a-Service (MaaS). However, transmitting raw text to servers raises critical privacy concerns. Existing approaches employ deep neural networks (DNNs) or differential privacy (DP) to perturb inputs. Yet, these approaches suff…

Cited by 0SourceScholar