Search Results for author:
Found 9 papers, 6 papers with code
IITKGP at W-NUT 2020 Shared Task-1: Domain specific BERT representation for Named Entity Recognition of lab protocol
Supervised models trained to predict properties from representations have been achieving high accuracy on a variety of tasks. For in-stance, the BERT family seems to work exceptionally well on the downstream task from NER tagging to the range of other linguistictasks.
Winners at W-NUT 2020 Shared Task-3: Leveraging Event Specific and Chunk Span information for Extracting COVID Entities from Tweets
Twitter has acted as an important source of information during disasters and pandemic, especially during the times of COVID-19.
Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States
Mining the causes of political decision-making is an active research area in the field of political science.
LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compression
Low Rank Decomposition of matrix - splitting a large matrix into a product of two smaller matrix offers a means for compression that reduces the parameters of a model without sparsification, and hence delivering more speedup on modern hardware.
Logical Fallacy Detection
In this paper, we propose the task of logical fallacy detection, and provide a new dataset (Logic) of logical fallacies generally found in text, together with an additional challenge set for detecting logical fallacies in climate change claims (LogicClimate).
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
The principle of independent causal mechanisms (ICM) states that generative processes of real world data consist of independent modules which do not influence or inform each other.
Hostility Detection in Hindi leveraging Pre-Trained Language Models
This paper harnesses attention based pre-trained models fine-tuned on Hindi data with Hostile-Non hostile task as Auxiliary and fusing its features for further sub-tasks classification.
Domain specific BERT representation for Named Entity Recognition of lab protocol
Supervised models trained to predict properties from representations have been achieving high accuracy on a variety of tasks.
Ranked #2 on
Named Entity Recognition (NER)
on WNUT 2020
Leveraging Event Specific and Chunk Span features to Extract COVID Events from tweets
Twitter has acted as an important source of information during disasters and pandemic, especially during the times of COVID-19.
