90 citations · 95 across the 4 of their papers we have counts for
6 papers · 1 filter
Bonafide at LegalLens 2024 Shared Task: Using Lightweight DeBERTa Based Encoder For Legal Violation Detection and Resolution
Shikha Bordia
In this work, we present two systems -- Named Entity Resolution (NER) and Natural Language Inference (NLI) -- for detecting legal violations within unstructured textual data and fo…
HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification
Yichen Jiang, Shikha Bordia, Zheng Zhong +3
We introduce HoVer (HOppy VERification), a dataset for many-hop evidence extraction and fact verification. It challenges models to extract facts from several Wikipedia articles tha…
Do Attention Heads in BERT Track Syntactic Dependencies?
Phu Mon Htut, Jason Phang, Shikha Bordia +1
We investigate the extent to which individual attention heads in pretrained transformer language models, such as BERT and RoBERTa, implicitly capture syntactic dependency relations…
Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs
Alex Warstadt, Yu Cao, Ioana Grosu +13
Though state-of-the-art sentence representation models can perform tasks requiring significant knowledge of grammar, it is an open question how best to evaluate their grammatical k…
Identifying and Reducing Gender Bias in Word-Level Language Models
Shikha Bordia, Samuel R. Bowman
Many text corpora exhibit socially problematic biases, which can be propagated or amplified in the models trained on such data. For example, doctor cooccurs more frequently with ma…
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…