24 citations · 49 across the 17 of their papers we have counts for
6 papers · 1 filter
Continuously Reliable Detection of New-Normal Misinformation: Semantic Masking and Contrastive Smoothing in High-Density Latent Regions
Abhijit Suprem, Joao Eduardo Ferreira, Calton Pu
Toxic misinformation campaigns have caused significant societal harm, e.g., affecting elections and COVID-19 information awareness. Unfortunately, despite successes of (gold standa…
EdnaML: A Declarative API and Framework for Reproducible Deep Learning
Abhijit Suprem, Sanjyot Vaidya, Avinash Venugopal +2
Machine Learning has become the bedrock of recent advances in text, image, video, and audio processing and generation. Most production systems deal with several models during deplo…
Evaluating Generalizability of Fine-Tuned Models for Fake News Detection
Abhijit Suprem, Calton Pu
The Covid-19 pandemic has caused a dramatic and parallel rise in dangerous misinformation, denoted an `infodemic' by the CDC and WHO. Misinformation tied to the Covid-19 infodemic…
MiDAS: Multi-integrated Domain Adaptive Supervision for Fake News Detection
Abhijit Suprem, Calton Pu
COVID-19 related misinformation and fake news, coined an 'infodemic', has dramatically increased over the past few years. This misinformation exhibits concept drift, where the dist…
Event Detection in Noisy Streaming Data with Combination of Corroborative and Probabilistic Sources
Abhijit Suprem, Calton Pu
Global physical event detection has traditionally relied on dense coverage of physical sensors around the world; while this is an expensive undertaking, there have not been alterna…
Concept Drift Detection and Adaptation with Weak Supervision on Streaming Unlabeled Data
Abhijit Suprem
Concept drift in learning and classification occurs when the statistical properties of either the data features or target change over time; evidence of drift has appeared in search…