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Redhot: A corpus of annotated medical questions, experiences, and claims on social media
We present Reddit Health Online Talk (RedHOT), a corpus of 22,000 richly annotated social
media posts from Reddit spanning 24 health conditions. Annotations include demarcations …
media posts from Reddit spanning 24 health conditions. Annotations include demarcations …
Crowdspeech and voxdiy: Benchmark datasets for crowdsourced audio transcription
Domain-specific data is the crux of the successful transfer of machine learning systems from
benchmarks to real life. In simple problems such as image classification, crowdsourcing has …
benchmarks to real life. In simple problems such as image classification, crowdsourcing has …
SemEval-2023 task 8: Causal medical claim identification and related PIO frame extraction from social media posts
Identification of medical claims from user-generated text data is an onerous but essential
step for various tasks including content moderation, and hypothesis generation. SemEval …
step for various tasks including content moderation, and hypothesis generation. SemEval …
Resolving the human subjects status of machine learning's crowdworkers
In recent years, machine learning (ML) has relied heavily on crowdworkers both for building
datasets and for addressing research questions requiring human interaction or judgment …
datasets and for addressing research questions requiring human interaction or judgment …
Data labeling for machine learning engineers: project-based curriculum and data-centric competitions
The process of training and evaluating machine learning (ML) models relies on high-quality
and timely annotated datasets. While a significant portion of academic and industrial …
and timely annotated datasets. While a significant portion of academic and industrial …
[PDF][PDF] Song describer: a platform for collecting textual descriptions of music recordings
ABSTRACT We present Song Describer, an open-source data annotation platform for
crowdsourcing textual descriptions of music recordings. Through this tool, we propose to …
crowdsourcing textual descriptions of music recordings. Through this tool, we propose to …
A Hard Nut to Crack: Idiom Detection with Conversational Large Language Models
In this work, we explore idiomatic language processing with Large Language Models
(LLMs). We introduce the Idiomatic language Test Suite IdioTS, a new dataset of difficult …
(LLMs). We introduce the Idiomatic language Test Suite IdioTS, a new dataset of difficult …
REGROW: Reimagining global crowdsourcing for better human-AI collaboration
Crowdworkers silently enable much of today's AI-based products, with several online
platforms offering a myriad of data labelling and content moderation tasks through …
platforms offering a myriad of data labelling and content moderation tasks through …
Hands-On Tutorial: Labeling with LLM and Human-in-the-Loop
Training and deploying machine learning models relies on a large amount of human-
annotated data. As human labeling becomes increasingly expensive and time-consuming …
annotated data. As human labeling becomes increasingly expensive and time-consuming …
[PDF][PDF] Robustifying NLP with Humans in the Loop
D Kaushik - 2022 - cs.cmu.edu
Despite machine learning (ML)'s many practical breakthroughs, formidable obstacles
obstruct its deployment in consequential applications. Modern ML models have repeatedly …
obstruct its deployment in consequential applications. Modern ML models have repeatedly …