Үштік шығын
Related Papers
Large-Scale Representation Learning from Visually Grounded Untranscribed Speech
AbstractSystems that can associate images with their spoken audio captions are an important step towards visually grounded language learning. We describe a scalable method to automatically generate diverse audio for …...
A Two-phase Prototypical Network Model for Incremental Few-shot Relation Classification
AbstractRelation Classification (RC) plays an important role in natural language processing (NLP). Current conventional supervised and distantly supervised RC models always make a closed-world assumption which ignores the emergence of …...
Pairwise Supervised Contrastive Learning of Sentence Representations
AbstractMany recent successes in sentence representation learning have been achieved by simply fine-tuning on the Natural Language Inference (NLI) datasets with triplet loss or siamese loss. Nevertheless, they share a …...
Privacy Regularization: Joint Privacy-Utility Optimization in LanguageModels
AbstractNeural language models are known to have a high capacity for memorization of training samples. This may have serious privacy im- plications when training models on user content such as …...
Hyperbolic Relevance Matching for Neural Keyphrase Extraction
AbstractKeyphrase extraction is a fundamental task in natural language processing that aims to extract a set of phrases with important information from a source document. Identifying important keyphrases is the …...
Improving Neural Models for Radiology Report Retrieval with Lexicon-based Automated Annotation
AbstractMany clinical informatics tasks that are based on electronic health records (EHR) need relevant patient cohorts to be selected based on findings, symptoms and diseases. Frequently, these conditions are described …...
YNU-HPCC at SemEval-2022 Task 2: Representing Multilingual Idiomaticity based on Contrastive Learning
AbstractThis paper will present the methods we use as the YNU-HPCC team in the SemEval-2022 Task 2, Multilingual Idiomaticity Detection and Sentence Embedding. We are involved in two subtasks, including …...
Improving Visual-Semantic Embedding with Adaptive Pooling and Optimization Objective
AbstractVisual-Semantic Embedding (VSE) aims to learn an embedding space where related visual and semantic instances are close to each other. Recent VSE models tend to design complex structures to pool …...