Search Results for author: Payam Karisani

Found 13 papers, 7 papers with code

Fact Checking Beyond Training Set

1 code implementation27 Mar 2024 Payam Karisani, Heng Ji

We then focus on the reader component and propose to train it such that it is insensitive towards the order of claims and evidence documents.

Domain Adaptation Fact Checking

Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain

no code implementations9 Feb 2024 Amin Karimi Monsefi, Payam Karisani, Mengxi Zhou, Stacey Choi, Nathan Doble, Heng Ji, Srinivasan Parthasarathy, Rajiv Ramnath

In this paper, we introduce a new neural network architecture, termed LoGoNet, with a tailored self-supervised learning (SSL) method to mitigate such challenges.

Contrastive Learning Image Segmentation +4

Named Entity Recognition Under Domain Shift via Metric Learning for Life Sciences

1 code implementation19 Jan 2024 Hongyi Liu, Qingyun Wang, Payam Karisani, Heng Ji

In our experiments, we observed that such a model is prone to mislabeling the source entities, which can often appear in the text, as the target entities.

Contrastive Learning Few-Shot Learning +4

Neural Networks Against (and For) Self-Training: Classification with Small Labeled and Large Unlabeled Sets

1 code implementation31 Dec 2023 Payam Karisani

To overcome this challenge, we propose a hybrid metric to replace the plain confidence measurement.

Language Modelling

Ericson: An Interactive Open-Domain Conversational Search Agent

no code implementations5 Apr 2023 ZiHao Wang, Ali Ahmadvand, Jason Choi, Payam Karisani, Eugene Agichtein

Open-domain conversational search (ODCS) aims to provide valuable, up-to-date information, while maintaining natural conversations to help users refine and ultimately answer information needs.

Conversational Search Dialogue Management +6

Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting

no code implementations9 Nov 2022 Chen Lin, Safoora Yousefi, Elvis Kahoro, Payam Karisani, Donghai Liang, Jeremy Sarnat, Eugene Agichtein

Most of the prior work relied on modeling pollutant concentrations collected from ground-based monitors and meteorological data for long-term forecasting of outdoor ozone, oxides of nitrogen, and PM2. 5.

Time Series Time Series Forecasting

Multi-View Active Learning for Short Text Classification in User-Generated Data

no code implementations5 Dec 2021 Payam Karisani, Negin Karisani, Li Xiong

Our model has three novelties: 1) It is the first approach to employ multi-view active learning in this domain.

Active Learning Language Modelling +2

Semi-Supervised Text Classification via Self-Pretraining

1 code implementation30 Sep 2021 Payam Karisani, Negin Karisani

This set is used to initialize the second classifier, to be further trained by the set of labeled documents.

Pseudo Label Semi-Supervised Text Classification

View Distillation with Unlabeled Data for Extracting Adverse Drug Effects from User-Generated Data

no code implementations NAACL (SMM4H) 2021 Payam Karisani, Jinho D. Choi, Li Xiong

Then a classifier is trained on each view to label a set of unlabeled documents to be used as an initializer for a new classifier in the other view.

Word Embeddings

Domain-Guided Task Decomposition with Self-Training for Detecting Personal Events in Social Media

no code implementations21 Apr 2020 Payam Karisani, Joyce C. Ho, Eugene Agichtein

Mining social media content for tasks such as detecting personal experiences or events, suffer from lexical sparsity, insufficient training data, and inventive lexicons.

General Classification Semi-Supervised Text Classification +1

Mining Coronavirus (COVID-19) Posts in Social Media

1 code implementation28 Mar 2020 Negin Karisani, Payam Karisani

World Health Organization (WHO) characterized the novel coronavirus (COVID-19) as a global pandemic on March 11th, 2020.

BIG-bench Machine Learning

Did You Really Just Have a Heart Attack? Towards Robust Detection of Personal Health Mentions in Social Media

2 code implementations26 Feb 2018 Payam Karisani, Eugene Agichtein

The first, critical, task for these applications is classifying whether a personal health event was mentioned, which we call the (PHM) problem.

Epidemiology Semi-Supervised Text Classification

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