10 papers
Regret minimization in Linear Bandits with offline data via extended D-optimal exploration
Sushant Vijayan, Arun Suggala, Karthikeyan Shanmugam +1
We consider the problem of online regret minimization in linear bandits with access to prior observations (offline data) from the underlying bandit model. There are numerous applic…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Improved Message Delivery in Mobile Maternal Health
Arpan Dasgupta, Mizhaan Maniyar, Awadhesh Srivastava +7
Mobile health (mHealth) programs utilize automated voice messages to deliver health information, particularly targeting underserved communities, demonstrating the effectiveness of…
A Personalized Exercise Assistant using Reinforcement Learning (PEARL): Results from a four-arm Randomized-controlled Trial
Amy Armento Lee, Narayan Hegde, Nina Deliu +16
Consistent physical inactivity poses a major global health challenge. Mobile health (mHealth) interventions, particularly Just-in-Time Adaptive Interventions (JITAIs), offer a prom…
Robust Reward Modeling via Causal Rubrics
Pragya Srivastava, Harman Singh, Rahul Madhavan +9
Reward models (RMs) are fundamental to aligning Large Language Models (LLMs) via human feedback, yet they often suffer from reward hacking. They tend to latch on to superficial or…
Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts?
Sravanti Addepalli, Yerram Varun, Arun Suggala +2
Large Language Models (LLMs) are known to be susceptible to crafted adversarial attacks or jailbreaks that lead to the generation of objectionable content despite being aligned to…