3 papers
cs.LG2026
Repurposing Adversarial Perturbations for Continual Learning: From Defense to Active Alignment
Ran Liu, Min Yu, Mingqi Liu +7
In dynamic environments, large language models need to keep adapting to new tasks, but continual learning often suffers from forgetting, limited transfer, and vulnerability to adve…
cs.CR2026
The Granularity Mismatch in Agent Security: Argument-Level Provenance Solves Enforcement and Isolates the LLM Reasoning Bottleneck
Linfeng Fan, Ziwei Li, Yuan Tian +3
Tool-using LLM agents must act on untrusted webpages, emails, files, and API outputs while issuing privileged tool calls. Existing defenses often mediate trust at the granularity o…
cs.CL2025
TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection
Yang Cao, Sikun Yang, Chen Li +5
Text anomaly detection is crucial for identifying spam, misinformation, and offensive language in natural language processing tasks. Despite the growing adoption of embedding-based…