collaborators

10 papers

cs.IR2026

Mood-Aware Music Recommendation: Integrating User Affective Signals into Ranking Systems

Terence Zeng, Abhishek K. Umrawal

Recommendation systems are essential in modern music streaming platforms due to the vast amount of available content. While collaborative filtering is widely used to suggest items…

cs.CL2026

A Theoretical Game of Attacks via Compositional Skills

Xinbo Wu, Huan Zhang, Abhishek Umrawal +1

As large language models grow increasingly capable, concerns about their safe deployment have intensified. While numerous alignment strategies aim to restrict harmful behavior, the…

cs.SI2026

A Pressure-Based Diffusion Model for Influence Maximization on Social Networks

Curt Stutsman, Eliot W. Robson, Abhishek K. Umrawal

In many real-world scenarios, an individual's local social network carries significant influence over the opinions they form and subsequently propagate. In this paper, we propose a…

cs.LG2026

DART: aDaptive Accept RejecT for non-linear top-K subset identification

Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn +1

We consider the bandit problem of selecting out of arms at each time step. The reward can be a non-linear function of the rewards of the selected individual arms. The direc…

cs.SI2026

A Community-Aware Framework for Influence Maximization with Explicit Accounting for Inter-Community Influence

Eliot W. Robson, Abhishek K. Umrawal

Influence Maximization (IM) seeks to identify a small set of seed nodes in a social network to maximize expected information spread under a diffusion model. While community-based a…

cs.LG2026

LOFA: Online Influence Maximization under Full-Bandit Feedback using Lazy Forward Selection

Jinyu Xu, Abhishek K. Umrawal

We study the problem of influence maximization (IM) in an online setting, where the goal is to select a subset of nodes$\unicode{x2014}$called the seed set$\unicode{x2014}$at each…