9 citations · 15 across the 6 of their papers we have counts for
7 papers · 1 filter
How Grounded is Wikipedia? A Study on Structured Evidential Support and Retrieval
William Walden, Kathryn Ricci, Miriam Wanner +4
Wikipedia is a critical resource for modern NLP, serving as a rich repository of up-to-date and citation-backed information on a wide variety of subjects. The reliability of Wikipe…
CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?
Jiefu Ou, William Gantt Walden, Kate Sanders +13
A core part of scientific peer review involves providing expert critiques that directly assess the scientific claims a paper makes. While it is now possible to automatically genera…
Adapting Coreference Resolution Models through Active Learning
Michelle Yuan, Patrick Xia, Chandler May +2
Neural coreference resolution models trained on one dataset may not transfer to new, low-resource domains. Active learning mitigates this problem by sampling a small subset of data…
LOME: Large Ontology Multilingual Extraction
Patrick Xia, Guanghui Qin, Siddharth Vashishtha +7
We present LOME, a system for performing multilingual information extraction. Given a text document as input, our core system identifies spans of textual entity and event mentions…
On Measuring Social Biases in Sentence Encoders
Chandler May, Alex Wang, Shikha Bordia +2
The Word Embedding Association Test shows that GloVe and word2vec word embeddings exhibit human-like implicit biases based on gender, race, and other social constructs (Caliskan et…
Streaming Word Embeddings with the Space-Saving Algorithm
Chandler May, Kevin Duh, Benjamin Van Durme +1
We develop a streaming (one-pass, bounded-memory) word embedding algorithm based on the canonical skip-gram with negative sampling algorithm implemented in word2vec. We compare our…
An Analysis of Lemmatization on Topic Models of Morphologically Rich Language
Chandler May, Ryan Cotterell, Benjamin Van Durme
Topic models are typically represented by top- word lists for human interpretation. The corpus is often pre-processed with lemmatization (or stemming) so that those representati…