198 citations · 353 across the 13 of their papers we have counts for
15 papers
CALRec: Contrastive Alignment of Generative LLMs for Sequential Recommendation
Yaoyiran Li, Xiang Zhai, Moustafa Alzantot +4
Traditional recommender systems such as matrix factorization methods have primarily focused on learning a shared dense embedding space to represent both items and user preferences.…
Multi-Task End-to-End Training Improves Conversational Recommendation
Naveen Ram, Dima Kuzmin, Ellie Ka In Chio +4
In this paper, we analyze the performance of a multitask end-to-end transformer model on the task of conversational recommendations, which aim to provide recommendations based on a…
PhysioGAN: Training High Fidelity Generative Model for Physiological Sensor Readings
Moustafa Alzantot, Luis Garcia, Mani Srivastava
Generative models such as the variational autoencoder (VAE) and the generative adversarial networks (GAN) have proven to be incredibly powerful for the generation of synthetic data…
VindiCo: Privacy Safeguard Against Adaptation Based Spyware in Human-in-the-Loop IoT
Salma Elmalaki, Bo-Jhang Ho, Moustafa Alzantot +2
Personalized IoT adapts their behavior based on contextual information, such as user behavior and location. Unfortunately, the fact that personalized IoT adapts to user context ope…
Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries
Sukhdeep S. Sodhi, Ellie Ka-In Chio, Ambarish Jash +18
As more and more online search queries come from voice, automatic speech recognition becomes a key component to deliver relevant search results. Errors introduced by automatic spee…
NeuronInspect: Detecting Backdoors in Neural Networks via Output Explanations
Xijie Huang, Moustafa Alzantot, Mani Srivastava
Deep neural networks have achieved state-of-the-art performance on various tasks. However, lack of interpretability and transparency makes it easier for malicious attackers to inje…