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Found 6 papers, 1 papers with code
KDDIE at SemEval-2022 Task 11: Using DeBERTa for Named Entity Recognition
In this work, we introduce our system to the SemEval 2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER) competition.
Transformer-based Approach for Document Understanding
We present an end-to-end transformer-based framework named TRDLU for the task of Document Layout Understanding (DLU).
Ranked #2 on
Document Layout Analysis
on PubLayNet val
Feature Selection for Learning to Predict Outcomes of Compute Cluster Jobs with Application to Decision Support
We present a supervised learning model trained on a Simple Linux Utility for Resource Management (Slurm) data set of HPC jobs using three different techniques for selecting features: linear regression, lasso, and ridge regression.
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks
As part of the experimental test bed for empirical evaluation of this approach, we created a merged multi-corpus data set for scientific publication layout detection tasks.
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science
This system meets computational information and knowledge management (CIKM) requirements of metadata-driven payload extraction, named entity extraction, and relationship extraction from text.
Machine Learning for Predictive Analytics of Compute Cluster Jobs
We address the problem of predicting whether sufficient memory and CPU resources have been requested for jobs at submission time.
