4 papers
GFlowRL: Scaling Distribution-Matching RL to Large Language Models
Xiaodong Liu, Michael Xu, Jack W. Stokes +3
Generative Flow Networks (GFlowNets) offer a promising alternative to reward-maximizing reinforcement learning (RL) for large reasoning models, encouraging diverse reasoning paths…
Argo: Efficient Importance Labeling for Enterprise Email Systems
Siddhant Ray, Ganesh Ananthanarayanan, Kevin Chian +5
Email importance labeling has long been a critical yet challenging problem for businesses and individuals. Traditional approaches; such as keyword matching, user-defined rules, and…
Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers
Andrew Zhao, Reshmi Ghosh, Vitor Carvalho +4
Large language model (LLM) systems increasingly power everyday AI applications such as chatbots, computer-use assistants, and autonomous robots, where performance often depends on…
VLMGuard: Bootstrapping Malicious Prompt Detectors from Unlabeled Vision-Language Prompts in the Wild
Junlin Fang, Wenyu Chen, Reshmi Ghosh +7
Vision-language Models (VLMs) are essential for contextual understanding of both visual and textual information. However, their vulnerability to adversarially manipulated inputs pr…