3 papers
cs.CL2026
ToolScope: Enhancing LLM Agent Tool Use through Tool Merging and Context-Aware Filtering
Marianne Menglin Liu, Daniel Garcia, Fjona Parllaku +3
Large language model (LLM) agents rely on external tools to solve complex tasks, but real-world toolsets often contain redundant tools with overlapping names and descriptions, intr…
cs.SE2025
Routesplain: Towards Faithful and Intervenable Routing for Software-related Tasks
Adam Štorek, Adam Å torek, Vikas Upadhyay +7
LLMs now tackle a wide range of software-related tasks, yet we show that their performance varies markedly both across and within these tasks. Routing user queries to the appropria…
cs.CL2025
RAG Makes Guardrails Unsafe? Investigating Robustness of Guardrails under RAG-style Contexts
Yining She, Daniel W. Peterson, Marianne Menglin Liu +4
With the increasing adoption of large language models (LLMs), ensuring the safety of LLM systems has become a pressing concern. External LLM-based guardrail models have emerged as…