Zobrazeno 1 - 10
of 353
pro vyhledávání: '"Pu, Calton"'
Toxic misinformation campaigns have caused significant societal harm, e.g., affecting elections and COVID-19 information awareness. Unfortunately, despite successes of (gold standard) retrospective studies of misinformation that confirmed their harmf
Externí odkaz:
http://arxiv.org/abs/2301.07981
Recent advances in text classification and knowledge capture in language models have relied on availability of large-scale text datasets. However, language models are trained on static snapshots of knowledge and are limited when that knowledge evolve
Externí odkaz:
http://arxiv.org/abs/2211.12508
Autor:
Suprem, Abhijit, Singh, Purva, Cherkadi, Suma, Vaidya, Sanjyot, Ferreira, Joao Eduardo, Pu, Calton
The vehicle recognition area, including vehicle make-model recognition (VMMR), re-id, tracking, and parts-detection, has made significant progress in recent years, driven by several large-scale datasets for each task. These datasets are often non-ove
Externí odkaz:
http://arxiv.org/abs/2211.09098
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 deployment and training, each with a variety of tuned hyperparameters. Furt
Externí odkaz:
http://arxiv.org/abs/2211.06783
Autor:
Suprem, Abhijit, Vaidya, Sanjyot, Cherkadi, Suma, Singh, Purva, Ferreira, Joao Eduardo, Pu, Calton
Machine learning models with explainable predictions are increasingly sought after, especially for real-world, mission-critical applications that require bias detection and risk mitigation. Inherent interpretability, where a model is designed from th
Externí odkaz:
http://arxiv.org/abs/2205.10011
Autor:
Suprem, Abhijit, Pu, Calton
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 distribution of fake news changes over time, reducing effectiveness of pre
Externí odkaz:
http://arxiv.org/abs/2205.09817
Autor:
Suprem, Abhijit, Pu, Calton
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 changes continuously; this can lead to performance degradation of fine
Externí odkaz:
http://arxiv.org/abs/2205.07154
A rapidly evolving situation such as the COVID-19 pandemic is a significant challenge for AI/ML models because of its unpredictability. %The most reliable indicator of the pandemic spreading has been the number of test positive cases. However, the te
Externí odkaz:
http://arxiv.org/abs/2011.05416
Autor:
Suprem, Abhijit, Pu, Calton
The Covid-19 pandemic has fundamentally altered many facets of our lives. With nationwide lockdowns and stay-at-home advisories, conversations about the pandemic have naturally moved to social networks, e.g. Twitter. This affords an unprecedented ins
Externí odkaz:
http://arxiv.org/abs/2010.04084
Publikováno v:
PVLDB, 13(11):2453-2465, 2020
Recent advances in computer vision have led to a resurgence of interest in visual data analytics. Researchers are developing systems for effectively and efficiently analyzing visual data at scale. A significant challenge that these systems encounter
Externí odkaz:
http://arxiv.org/abs/2009.05440