3 papers
cs.AI2026
The Harness Effect: How Orchestration Design Sets the Token Economics of Enterprise Agentic AI
Muayad Sayed Ali, Aliaksandra Novik, Anji Boddupally +29
Agentic AI development today runs on token maxing: buying capability with tokens -- longer reasoning traces, more turns, wider tool payloads, bigger replayed contexts -- so tokens…
cs.CL2026
Accurate Failure Prediction in Agents Does Not Imply Effective Failure Prevention
Rakshith Vasudev, Melisa Russak, Dan Bikel +1
Proactive interventions by LLM critic models are often assumed to improve reliability, yet their effects at deployment time are poorly understood. We show that a binary LLM critic…
cs.LG2025
Benchmarking Neural Network Training Algorithms
George E. Dahl, Frank Schneider, Zachary Nado +22
Training algorithms, broadly construed, are an essential part of every deep learning pipeline. Training algorithm improvements that speed up training across a wide variety of workl…