3 citations · 8 across the 10 of their papers we have counts for
11 papers
IntentTune: Using user demand and personalization to resolve "unknown" query intents for e-commerce search
Rachith Aiyappa, Ishita Khan, Chester Palen-Michel +4
Understanding user intent is fundamental to delivering relevant search results in e-commerce. However, substantial fraction of real-world queries are under-specified (e.g., "watch"…
Comparing Approaches to Automatic Summarization in Less-Resourced Languages
Chester Palen-Michel, Constantine Lignos
Automatic text summarization has achieved high performance in high-resourced languages like English, but comparatively less attention has been given to summarization in less-resour…
OpenNER 1.0: Standardized Open-Access Named Entity Recognition Datasets in 50+ Languages
Chester Palen-Michel, Maxwell Pickering, Maya Kruse +2
We present OpenNER 1.0, a standardized collection of openly-available named entity recognition (NER) datasets. OpenNER contains 36 NER corpora that span 52 languages, human-annotat…
Investigating LLM Applications in E-Commerce
Chester Palen-Michel, Ruixiang Wang, Yipeng Zhang +3
The emergence of Large Language Models (LLMs) has revolutionized natural language processing in various applications especially in e-commerce. One crucial step before the applicati…
QueryNER: Segmentation of E-commerce Queries
Chester Palen-Michel, Lizzie Liang, Zhe Wu +1
We present QueryNER, a manually-annotated dataset and accompanying model for e-commerce query segmentation. Prior work in sequence labeling for e-commerce has largely addressed asp…
LR-Sum: Summarization for Less-Resourced Languages
Chester Palen-Michel, Constantine Lignos
This preprint describes work in progress on LR-Sum, a new permissively-licensed dataset created with the goal of enabling further research in automatic summarization for less-resou…
MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder +42
African languages are spoken by over a billion people, but are underrepresented in NLP research and development. The challenges impeding progress include the limited availability o…
Toward More Meaningful Resources for Lower-resourced Languages
Constantine Lignos, Nolan Holley, Chester Palen-Michel +1
In this position paper, we describe our perspective on how meaningful resources for lower-resourced languages should be developed in connection with the speakers of those languages…
Multilingual Open Text Release 1: Public Domain News in 44 Languages
Chester Palen-Michel, June Kim, Constantine Lignos
We present Multilingual Open Text (MOT), a new multilingual corpus containing text in 44 languages, many of which have limited existing text resources for natural language processi…
SeqScore: Addressing Barriers to Reproducible Named Entity Recognition Evaluation
Chester Palen-Michel, Nolan Holley, Constantine Lignos
To address a looming crisis of unreproducible evaluation for named entity recognition, we propose guidelines and introduce SeqScore, a software package to improve reproducibility.…
MasakhaNER: Named Entity Recognition for African Languages
David Ifeoluwa Adelani, Jade Abbott, Graham Neubig +58
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named en…