2 papers
cs.AI2026
Reproducing and Stress-Testing Two Approaches to LLM Reasoning Reliability: Test-Time Probability Aggregation and Logic-Representation Editing
Minhan Cho, Jimin Kweon
We independently reproduce two recent methods for making large language model (LLM) reasoning more reliable, and stress-test them across domains and models (RPC across four new tas…
cs.AI2026
LLM within MCP Matters: Measuring Inefficient Resource Utilization Driven by LLMs
Minhan Cho, Soyoung Park, Kihyeon Jeong +3
The Model Context Protocol (MCP) standardizes how servers expose data and tools to Large Language Models (LLMs). A common server design embeds frequently used reference data, such…