17 citations · 36 across the 28 of their papers we have counts for
10 papers · 1 filter
ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval
David H. Yang, Yuxuan Zhu, Mohammad Mohammadi Amiri +4
Large language models (LLMs) have shown great performance on complex reasoning tasks but often require generating long intermediate thoughts before reaching a final answer. During…
Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use
Yiyang Li, Zehong Wang, Zhengqing Yuan +4
Illicit drug use among teenagers and young adults (TYAs) remains a pressing public health concern, with rising prevalence and long-term impacts on health and well-being. To detect…
PEEL the Layers and Find Yourself: Revisiting Inference-time Data Leakage for Residual Neural Networks
Huzaifa Arif, Keerthiram Murugesan, Payel Das +2
This paper explores inference-time data leakage risks of deep neural networks (NNs), where a curious and honest model service provider is interested in retrieving users' private da…
Combinatorial Multi-armed Bandits: Arm Selection via Group Testing
Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan +2
This paper considers the problem of combinatorial multi-armed bandits with semi-bandit feedback and a cardinality constraint on the super-arm size. Existing algorithms for solving…
STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models
Shreyas Basavatia, Keerthiram Murugesan, Shivam Ratnakar
Interactive fiction games have emerged as an important application to improve the generalization capabilities of language-based reinforcement learning (RL) agents. Existing environ…
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
Shuai Zhang, Heshan Devaka Fernando, Miao Liu +5
This paper studies the transfer reinforcement learning (RL) problem where multiple RL problems have different reward functions but share the same underlying transition dynamics. In…