12 citations · 17 across the 7 of their papers we have counts for
9 papers
PyTAIL: Interactive and Incremental Learning of NLP Models with Human in the Loop for Online Data
Shubhanshu Mishra, Jana Diesner
Online data streams make training machine learning models hard because of distribution shift and new patterns emerging over time. For natural language processing (NLP) tasks that u…
NTULM: Enriching Social Media Text Representations with Non-Textual Units
Jinning Li, Shubhanshu Mishra, Ahmed El-Kishky +2
On social media, additional context is often present in the form of annotations and meta-data such as the post's author, mentions, Hashtags, and hyperlinks. We refer to these annot…
TweetNERD -- End to End Entity Linking Benchmark for Tweets
Shubhanshu Mishra, Aman Saini, Raheleh Makki +3
Named Entity Recognition and Disambiguation (NERD) systems are foundational for information retrieval, question answering, event detection, and other natural language processing (N…
Robust Candidate Generation for Entity Linking on Short Social Media Texts
Liam Hebert, Raheleh Makki, Shubhanshu Mishra +3
Entity Linking (EL) is the gateway into Knowledge Bases. Recent advances in EL utilize dense retrieval approaches for Candidate Generation, which addresses some of the shortcomings…
BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing
Jason Alan Fries, Leon Weber, Natasha Seelam +40
Training and evaluating language models increasingly requires the construction of meta-datasets --diverse collections of curated data with clear provenance. Natural language prompt…
LMSOC: An Approach for Socially Sensitive Pretraining
Vivek Kulkarni, Shubhanshu Mishra, Aria Haghighi
While large-scale pretrained language models have been shown to learn effective linguistic representations for many NLP tasks, there remain many real-world contextual aspects of la…