3 citations · 6 across the 5 of their papers we have counts for
5 papers
Comparing and combining some popular NER approaches on Biomedical tasks
Harsh Verma, Sabine Bergler, Narjesossadat Tahaei
We compare three simple and popular approaches for NER: 1) SEQ (sequence-labeling with a linear token classifier) 2) SeqCRF (sequence-labeling with Conditional Random Fields), and…
CLaC at SemEval-2023 Task 2: Comparing Span-Prediction and Sequence-Labeling approaches for NER
Harsh Verma, Sabine Bergler
This paper summarizes the CLaC submission for the MultiCoNER 2 task which concerns the recognition of complex, fine-grained named entities. We compare two popular approaches for NE…
CLaCLab at SocialDisNER: Using Medical Gazetteers for Named-Entity Recognition of Disease Mentions in Spanish Tweets
Harsh Verma, Parsa Bagherzadeh, Sabine Bergler
This paper summarizes the CLaC submission for SMM4H 2022 Task 10 which concerns the recognition of diseases mentioned in Spanish tweets. Before classifying each token, we encode ea…
Rethinking Evaluation Methodology for Audio-to-Score Alignment
John Thickstun, Jennifer Brennan, Harsh Verma
This paper offers a precise, formal definition of an audio-to-score alignment. While the concept of an alignment is intuitively grasped, this precision affords us new insight into…
Convolutional Composer Classification
Harsh Verma, John Thickstun
This paper investigates end-to-end learnable models for attributing composers to musical scores. We introduce several pooled, convolutional architectures for this task and draw con…