270 citations · 835 across the 84 of their papers we have counts for
8 papers · 1 filter
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…
Time-Reversal Provides Unsupervised Feedback to LLMs
Yerram Varun, Rahul Madhavan, Sravanti Addepalli +3
Large Language Models (LLMs) are typically trained to predict in the forward direction of time. However, recent works have shown that prompting these models to look back and critiq…
Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health Program
Arpan Dasgupta, Gagan Jain, Arun Suggala +3
Mobile health (mHealth) programs face a critical challenge in optimizing the timing of automated health information calls to beneficiaries. This challenge has been formulated as a…
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…
Linear Causal Representation Learning from Unknown Multi-node Interventions
Burak Varıcı, Emre Acartürk, Karthikeyan Shanmugam +1
Despite the multifaceted recent advances in interventional causal representation learning (CRL), they primarily focus on the stylized assumption of single-node interventions. This…
Glauber Generative Model: Discrete Diffusion Models via Binary Classification
Harshit Varma, Dheeraj Nagaraj, Karthikeyan Shanmugam
We introduce the Glauber Generative Model (GGM), a new class of discrete diffusion models, to obtain new samples from a distribution given samples from a discrete space. GGM deploy…
A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food
Conor M. Artman, Aditya Mate, Ezinne Nwankwo +10
We developed a common algorithmic solution addressing the problem of resource-constrained outreach encountered by social change organizations with different missions and operations…
Score-based Causal Representation Learning: Linear and General Transformations
Burak Varıcı, Emre Acartürk, Karthikeyan Shanmugam +2
This paper addresses intervention-based causal representation learning (CRL) under a general nonparametric latent causal model and an unknown transformation that maps the latent va…