4 papers
Tracing Target Answers in Poisoned Retrieval Corpora via Token Influence Attribution
Yan-Lun Chen, Pin-Yu Chen, Chia-Mu Yu +3
Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate model outputs through malicious retrieved documents. Existing detection meth…
CodeSentinel: A Three-Layer Defense Against Indirect Prompt Injection in Code Contexts
Po-Han Cheng, Chia-Mu Yu, Ying-Dar Lin +2
Code large language models increasingly retrieve external code context from repositories, documentation, issue threads, and coding-agent environments, creating an indirect prompt-i…
Beyond Natural Language Perplexity: Detecting Dead Code Poisoning in Code Generation Datasets
Chi-Chien Tsai, Chia-Mu Yu, Ying-Dar Lin +2
The increasing adoption of large language models (LLMs) for code-related tasks has raised concerns about the security of their training datasets. One critical threat is dead code p…
Layer-Aware Task Arithmetic: Disentangling Task-Specific and Instruction-Following Knowledge
Yan-Lun Chen, Yi-Ru Wei, Chia-Yi Hsu +5
Large language models (LLMs) demonstrate strong task-specific capabilities through fine-tuning, but merging multiple fine-tuned models often leads to degraded performance due to ov…