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cs.IR2026
From Valid to Useful: Post-Verification Acquisition for Recursive Self-Improving Recommendation
Tonmoy Hasan, Taylor Foust, Shao Tang +6
Sequential recommenders can generate synthetic interaction sequences and retrain on the augmented corpus in a recursive self-improvement loop. To limit error accumulation, current…
cs.CL2026
Building Customer Support AI Agents at 100M-User Scale: An Evaluation-Driven Framework
Aman Gupta, Kevin Rossell, Edesio Alcobaça +8
The rapid rise in LLM capabilities has made AI agents increasingly viable across a broad range of tasks. Among the most promising applications is building production-ready customer…
cs.LG2026
Bayesian Preference Learning for Test-Time Steerable Reward Models
Jiwoo Hong, Shao Tang, Zhipeng Wang
Reward models are central to aligning language models with human preferences via reinforcement learning (RL). As RL is increasingly applied to settings such as verifiable rewards a…