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Found 15 papers, 11 papers with code
EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction
Multi-triple extraction is a challenging task due to the existence of informative inter-triple correlations, and consequently rich interactions across the constituent entities and relations. While existing works only explore entity representations, we propose to explicitly introduce relation representation, jointly represent it with entities, and novelly align them to identify valid triples. We perform comprehensive experiments on document-level relation extraction and joint entity and relation extraction along with ablations to demonstrate the advantage of the proposed method.
Document-level Relation Extraction
Joint Entity and Relation Extraction
$k$NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference
In-Context Learning (ICL), which formulates target tasks as prompt completion conditioned on in-context demonstrations, has become the prevailing utilization of LLMs.
Intra-class Adaptive Augmentation with Neighbor Correction for Deep Metric Learning
They have overlooked the wide characteristic changes of different classes and can not model abundant intra-class variations for generations.
ABINet++: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Spotting
In this paper, we argue that the limited capacity of language models comes from 1) implicit language modeling; 2) unidirectional feature representation; and 3) language model with noise input.
UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction
Relational triple extraction is challenging for its difficulty in capturing rich correlations between entities and relations.
Ranked #1 on
Relation Extraction
on WebNLG
Improving Chinese Spelling Check by Character Pronunciation Prediction: The Effects of Adaptivity and Granularity
In this paper, we consider introducing an auxiliary task of Chinese pronunciation prediction (CPP) to improve CSC, and, for the first time, systematically discuss the adaptivity and granularity of this auxiliary task.
DSE-GAN: Dynamic Semantic Evolution Generative Adversarial Network for Text-to-Image Generation
Text-to-image generation aims at generating realistic images which are semantically consistent with the given text.
Negative-Aware Attention Framework for Image-Text Matching
Image-text matching, as a fundamental task, bridges the gap between vision and language.
Lesion-Aware Transformers for Diabetic Retinopathy Grading
First, to the best of our knowledge, this is the first work to formulate lesion discovery as a weakly supervised lesion localization problem via a transformer decoder.
Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition
Additionally, based on the ensemble of iterative predictions, we propose a self-training method which can learn from unlabeled images effectively.
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction
Our experiments demonstrate the usefulness of the proposed entity structure and the effectiveness of SSAN.
Ranked #3 on
Relation Extraction
on DocRED
Overcoming Language Priors with Self-supervised Learning for Visual Question Answering
Our method can compensate for the data biases by generating balanced data without introducing external annotations.
Image Captioning with Context-Aware Auxiliary Guidance
Image captioning is a challenging computer vision task, which aims to generate a natural language description of an image.
Curriculum Learning for Natural Language Understanding
With the great success of pre-trained language models, the pretrain-finetune paradigm now becomes the undoubtedly dominant solution for natural language understanding (NLU) tasks.
Graph Structured Network for Image-Text Matching
The GSMN explicitly models object, relation and attribute as a structured phrase, which not only allows to learn correspondence of object, relation and attribute separately, but also benefits to learn fine-grained correspondence of structured phrase.
Ranked #13 on
Cross-Modal Retrieval
on Flickr30k
