collaborators

5 papers

cs.CL2026

When Do LLMs Replace Fine-Tuned NLU? A Decision Framework for Intent Detection in Production Conversational Systems

Carson Rodrigues, Oysturn Vas

A common claim is that zero-shot large language models (LLMs) can replace fine-tuned NLU classifiers for intent detection. We test this claim head-to-head and find that the honest…

cs.CV2026

Predicted Cortex Is Not a Domain-General Prior: A Matched-Control Audit of Brain-Encoding Features for Video Memorability

Carson Rodrigues

Brain-encoding foundation models predict fMRI responses to video, audio and text well enough to win the Algonauts 2025 challenge. We ask whether their predicted responses, obtained…

cs.SE2026

MCP Server Architecture Patterns for LLM-Integrated Applications

Carson Rodrigues, Oysturn Vas

The Model Context Protocol (MCP), introduced by Anthropic in November 2024, defines a standardized interface for connecting large language models (LLMs) to external tools, data sou…

cs.LG2026

When Is an LLM Worth It for Hyperparameter Optimization? A Budget-Matched Study on Tabular Data Finds the Warm-Start Is a Default Configuration, Not the Model

Carson Rodrigues, Oysturn Vas, Isaiah Abner DCosta +1

Large language models (LLMs) have been proposed as hyperparameter-optimization (HPO) advisors that "warm-start" search from prior knowledge, proposing strong configurations in very…

cs.AI2026

Hallucination as Context Drift: Synchronization Protocols for Multi-Agent LLM Systems

Carson Rodrigues

Multi-agent LLM systems routinely produce hallucinated outputs that cannot be explained by model deficiencies alone. A significant class of these failures arises not from model inc…