5 papers
Why Do AI Agents Break Rules? How Framing, Context, and Social Signals Shape Compliance
Mika Okamoto, Ansel Kaplan Erol, Kutluhan Erol
Specifying a penalty can turn a legal obligation into a cost-benefit calculation that favors violation. We show that this enforcement information paradox occurs in AI agents. Most…
Capability Provenance in Language Models: A Case Study in Social Reasoning
Glenn Matlin, Chandreyi Chakraborty, Saehee Eom +8
We use training-data attribution as an interpretable tool for capability discovery, mapping which regions of the pretraining corpus support social-reasoning versus STEM-reasoning i…
Explainable Model Routing for Agentic Workflows
Mika Okamoto, Ansel Kaplan Erol, Mark Riedl
Modern agentic workflows decompose complex tasks into specialized subtasks and route them to diverse models to minimize cost without sacrificing quality. However, current routing a…
Trust by Design: Skill Profiles for Transparent, Cost-Aware LLM Routing
Mika Okamoto, Ansel Kaplan Erol, Glenn Matlin
How should Large Language Model (LLM) practitioners select the right model for a task without wasting money? We introduce BELLA (Budget-Efficient LLM Selection via Automated skill-…
Finance Language Model Evaluation (FLaME)
Glenn Matlin, Mika Okamoto, Huzaifa Pardawala +2
Language Models (LMs) have demonstrated impressive capabilities with core Natural Language Processing (NLP) tasks. The effectiveness of LMs for highly specialized knowledge-intensi…