Semantic Relation Classification via Bidirectional LSTM Networks with Entity-aware Attention using Latent Entity Typing

roomylee/entity-aware-relation-classification • • 23 Jan 2019

Our model not only utilizes entities and their latent types as features effectively but also is more interpretable by visualizing attention mechanisms applied to our model and results of LET.

SciBERT: A Pretrained Language Model for Scientific Text

allenai/scibert • • IJCNLP 2019

Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive.

A Novel Cascade Binary Tagging Framework for Relational Triple Extraction

weizhepei/CasRel • • ACL 2020

Extracting relational triples from unstructured text is crucial for large-scale knowledge graph construction.

Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

stanfordnlp/stanza • • ACL 2020

We introduce Stanza, an open-source Python natural language processing toolkit supporting 66 human languages.

LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding

microsoft/unilm • • ACL 2021

Pre-training of text and layout has proved effective in a variety of visually-rich document understanding tasks due to its effective model architecture and the advantage of large-scale unlabeled scanned/digital-born documents.

Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets

ncbi-nlp/NCBI_BERT • • WS 2019

DocRED: A Large-Scale Document-Level Relation Extraction Dataset

thunlp/DocRED • • ACL 2019

Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs.

Are Transformers Effective for Time Series Forecasting?

cure-lab/ltsf-linear • • 26 May 2022

Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task.

A General Framework for Information Extraction using Dynamic Span Graphs

luanyi/DyGIE • • NAACL 2019

We introduce a general framework for several information extraction tasks that share span representations using dynamically constructed span graphs.

Simple BERT Models for Relation Extraction and Semantic Role Labeling

Impavidity/relogic • • 10 Apr 2019

We present simple BERT-based models for relation extraction and semantic role labeling.