9 papers
Evaluating LLMs in Database Scenarios: A Lifecycle Benchmark for Assessing Their Potential in Core Database Tasks
Shunfan Zheng, Dongsheng Shi, Yue Li +3
Large Language Models (LLMs) are transforming database interaction paradigms, evolving from simple query translators to autonomous database administrators (DBAs). However, current…
Construction-Driven Injection: Linguistically-Grounded Edit-Based Code-Mixing Fingerprints for Large Language Models
Yongyi Cui, Yue Li, Tianbao Jiang +1
Large language models (LLMs) are costly intellectual assets that remain exposed to unauthorized redistribution and commercial misuse. Injected fingerprints, i.e., trigger--target p…
Reinforcement Learning for Large Language Model Selective Evidence Adoption from Contaminated Retrieval Results
Yanyu Chen, Yue Li, Yongyi Cui +2
Retrieval-augmented large language models frequently face contexts that interleave useful evidence with misleading statements or instruction-like content. Blanket refusal discards…
From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration
Jiaqi Shi, Yuechan Li, Xulong Zhang +2
High-resolution Multimodal Large Language Models (MLLMs) face prohibitive computational costs during inference due to the explosion of visual tokens. Existing acceleration strategi…
AGMark: Attention-Guided Dynamic Watermarking for Large Vision-Language Models
Yue Li, Xin Yi, Dongsheng Shi +3
Watermarking has emerged as a pivotal solution for content traceability and intellectual property protection in large vision language models (LVLMs). However, vision-agnostic water…
Unified Defense for Large Language Models against Jailbreak and Fine-Tuning Attacks in Education
Xin Yi, Yue Li, Dongsheng Shi +3
Large Language Models (LLMs) are increasingly integrated into educational applications. However, they remain vulnerable to jailbreak and fine-tuning attacks, which can compromise s…
From Construction to Injection: Edit-Based Fingerprints for Large Language Models
Yue Li, Xin Yi, Dongsheng Shi +3
Reliable model fingerprints are essential for protecting large language models (LLMs) against unauthorized redistribution and commercial misuse. In black-box deployment, verificati…
Hierarchical Safety Realignment: Lightweight Restoration of Safety in Pruned Large Vision-Language Models
Yue Li, Xin Yi, Dongsheng Shi +3
With the increasing size of Large Vision-Language Models (LVLMs), network pruning techniques aimed at compressing models for deployment in resource-constrained environments have ga…
Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks
Xin Yi, Yue Li, Dongsheng Shi +3
Ensuring safety alignment is a critical requirement for large language models (LLMs), particularly given increasing deployment in real-world applications. Despite considerable adva…