collaborators

6 papers

cs.AI2026

Expected Free Energy as Belief-Dependent Utility for rho-POMDPs

Patrick Cooper, Alvaro Velasquez

An agent acting under partial observability must decide when to gather information and which observations are worth their cost. Standard POMDPs value information only through its e…

cs.AI2026

Narration-of-Thought: Inference-Time Scaffolding for Defeasible Ethical Reasoning in Large Language Models

Patrick Cooper, Alvaro Velasquez

Standard chain-of-thought on moral dilemmas exhibits two failure modes: stakeholder collapse (the trace names at most one party with a stake in the outcome) and uncertainty suppres…

cs.LG2026

Active Causal Experimentalist (ACE): Learning Intervention Strategies via Direct Preference Optimization

Patrick Cooper, Alvaro Velasquez

Discovering causal relationships requires controlled experiments, but experimentalists face a sequential decision problem: each intervention reveals information that should inform…

cs.AI2026

DeFAb: A Verifiable Benchmark for Defeasible Abduction in Foundation Models

Patrick Cooper, Alvaro Velasquez

A rule-based logic solver resolves every instance in our benchmark in under 50 microseconds with 100% accuracy; the best frontier language model reaches 65% at best and drops to 23…

cs.LG2026

KV-Fold: One-Step KV-Cache Recurrence for Long-Context Inference

Alireza Nadali, Patrick Cooper, Ashutosh Trivedi +1

We introduce KV-Fold, a simple, training-free long-context inference protocol that treats the key-value (KV) cache as the accumulator in a left fold over sequence chunks. At each s…

cs.CL2026

Monotonicity as an Architectural Bias for Robust Language Models

Patrick Cooper, Alireza Nadali, Ashutosh Trivedi +1

Large language models (LLMs) are known to exhibit brittle behavior under adversarial prompts and jailbreak attacks, even after extensive alignment and fine-tuning. This fragility r…