2 papers
cs.CL2026
Correcting Selection Bias in Sparse User Feedback for Large Language Model Quality Estimation: A Multi-Agent Hierarchical Bayesian Approach
Andrea Morandi, Mahesh Viswanathan
[Abridged] Production LLM deployments receive feedback from a non-random fraction of users: thumbs sit mostly in the tails of the satisfaction distribution, and a naive average ove…
cs.AI2026
From Intent to Execution: Composing Agentic Workflows with Agent Recommendation
Kishan Athrey, Ramin Pishehvar, Brian Riordan +1
Multi-Agent Systems (MAS) built using AI agents fulfill a variety of user intents that may be used to design and build a family of related applications. However, the creation of su…