11 citations · 13 across the 3 of their papers we have counts for
4 papers
Plan, Watch, Recover: A Benchmark and Architectures for Proactive Procedural Assistance
Kaustav Kundu, Ritvik Shrivastava, Maxim Arap +13
We envision a proactive multi-modal assistant system which gives users real-time step-by-step guidance on a procedural task, autonomously deciding \textit{when} to interrupt, and \…
Improving Model Factuality with Fine-grained Critique-based Evaluator
Yiqing Xie, Wenxuan Zhou, Pradyot Prakash +9
Factuality evaluation aims to detect factual errors produced by language models (LMs) and hence guide the development of more factual models. Towards this goal, we train a factuali…
Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learning
Aditya Srinivas Timmaraju, Mehdi Mashayekhi, Mingliang Chen +9
Variances in ad impression outcomes across demographic groups are increasingly considered to be potentially indicative of algorithmic bias in personalized ads systems. While there…
Reclaimer: A Reinforcement Learning Approach to Dynamic Resource Allocation for Cloud Microservices
Quintin Fettes, Avinash Karanth, Razvan Bunescu +2
Many cloud applications are migrated from the monolithic model to a microservices framework in which hundreds of loosely-coupled microservices run concurrently, with significant be…