collaborators

5 papers

cs.AI2026

CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions

Vanessa Figueiredo, Wilter Franceschi

Reliability in large language model (LLM) systems is typically framed as a function of model capability. We challenge this by demonstrating that reliability is significantly influe…

cs.AI2025

Symbolically Scaffolded Play: Designing Role-Sensitive Prompts for Generative NPC Dialogue

Vanessa Figueiredo, David Elumeze

Large Language Models (LLMs) promise to transform interactive games by enabling non-player characters (NPCs) to sustain unscripted dialogue. Yet it remains unclear whether constrai…

cs.AI2025

Fuzzy, Symbolic, and Contextual: Enhancing LLM Instruction via Cognitive Scaffolding

Vanessa Figueiredo

We study how prompt-level inductive biases influence the cognitive behavior of large language models (LLMs) in instructional dialogue. We introduce a symbolic scaffolding method pa…

cs.HC2025

Designing Smarter Conversational Agents for Kids: Lessons from Cognitive Work and Means-Ends Analyses

Vanessa Figueiredo

This paper presents two studies on how Brazilian children (ages 9--11) use conversational agents (CAs) for schoolwork, discovery, and entertainment, and how structured scaffolds ca…

cs.AI2025

A Fuzzy Logic Prompting Framework for Large Language Models in Adaptive and Uncertain Tasks

Vanessa Figueiredo

We introduce a modular prompting framework that supports safer and more adaptive use of large language models (LLMs) across dynamic, user-centered tasks. Grounded in human learning…