The Delegation Blind Spot: Auditing Product Decisions from Agent Choices
The Delegation Blind Spot: Auditing Product Decisions from Agent Choices This research investigates whether the actions taken by AI agents—such as booking a...
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The Delegation Blind Spot: Auditing Product Decisions from Agent Choices This research investigates whether the actions taken by AI agents—such as booking a...
Type-Safe Is Not Error-Free: A Constrained Decision Head Follows the Option Name, Not the Rubric Bound to It This paper investigates a critical vulnerability...
CliffCompaction: Cost-Efficient Compaction for Long-Horizon Coding Agents Coding agents often struggle with long-running tasks that require millions of token...
REFLEX with Jev for Efficient Selective Control in LLM Agents LLM agents often rely on powerful, expensive models to handle every step of a task, from simple...
SWE-Serve: Benchmarking Agentic Engineering For Production Inference Serving The researchers behind SWE-Serve have introduced a new benchmark designed to eva...
Quantum-Aided Active Device Detection in Energy-Harvesting Symbiotic Radio Networks This research addresses the challenge of managing massive numbers of Inte...
Reproducible AI Requires Reproducible Randomness This paper investigates a critical challenge in scientific computing and artificial intelligence: the assump...
Neutral-Atom-based Quantum Optimization for Resource Allocation in NOMA Networks This research explores how to solve complex resource management problems in...
JEV-as-a-Judge: Accept When Confident, Escalate When Unsure As AI systems increasingly rely on "LLM-as-a-judge" to evaluate tasks like coding, reasoning, and...
Large language model (LLM) agents often perform repetitive tasks, yet they typically rely on the model to "re-think" the same control decisions—such as how t...
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