Artificial Intelligence and Innovation Ecosystem: Evolutionary Developments, Challenges, and Future Directions explores how the integration of Artificial Int...
Dynamic Capability Scoping for Enterprise AI Agents: A Synthetic Dataset and Three-Source Permission Architecture Enterprise AI agents are often given a "sta...
A Roadmap to Impactful Pluralistic Alignment Research argues that while the field of pluralistic AI—the effort to make models that reflect diverse human valu...
Explainable Reinforcement Learning for assisting Air Traffic Controllers This research explores how to make Reinforcement Learning (RL) systems more transpar...
How Rules Represent Causal Knowledge: Causal Modeling with Probabilistic Logic Programming This paper addresses a fundamental challenge in artificial intelli...
Identifying Good Rules for Efficient SAT Encodings of Single-Constant Multiplication Using Machine Learning The Single Constant Multiplication (SCM) problem...
Beyond Sycophancy: Structured Resistance and Compliance in LLM Moral Reasoning This paper explores why large language models (LLMs) often change their opinio...
Answer Set Programming (ASP) has become significantly more powerful by incorporating linear constraints, allowing it to solve complex real-world problems.
Generative models are increasingly used to predict how complex systems evolve, but they often struggle to balance statistical likelihood with real-world rule...
Train the Model, Not the Reader: Decodability Supervision for Verifiable Activation Explanations This paper investigates a critical flaw in how we currently...
