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cs.CL2026
AI Security Beyond Core Domains: Resume Screening as a Case Study of Adversarial Vulnerabilities in Specialized LLM Applications
Honglin Mu, Jinghao Liu, Kaiyang Wan +4
Large Language Models (LLMs) excel at text comprehension and generation, making them ideal for automated tasks like code review and content moderation. However, our research identi…
cs.CL2025
Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching
Mingzhe Li, Jing Xiang, Qishen Zhang +2
Knowledge distillation typically involves transferring knowledge from a Large Language Model (LLM) to a Smaller Language Model (SLM). However, in tasks such as text matching, fine-…
cs.CL2025
Evaluate Bias without Manual Test Sets: A Concept Representation Perspective for LLMs
Lang Gao, Kaiyang Wan, Wei Liu +6
Bias in Large Language Models (LLMs) significantly undermines their reliability and fairness. We focus on a common form of bias: when two reference concepts in the model's concept…