论文阅读：《a simple but tough-to-beat baseline for sentence embeddings》 - 代码天地

论文阅读：《a simple but tough-to-beat baseline for sentence embeddings》

其他 2018-10-31 06:51:24 阅读次数: 0

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转载自blog.csdn.net/u011239443/article/details/83349071

论文阅读：《a simple but tough-to-beat baseline for sentence embeddings》

文献阅读笔记 # SimCSE: Simple Contrastive Learning of Sentence Embeddings

Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps —— 论文阅读笔记

论文阅读 | Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

论文解读：PromptBERT: Improving BERT Sentence Embeddings with Prompts

UNE BASE SIMPLE MAIS PARFAITE POUR SENTENCE EMBEDDINGS(一个简单但很难超越的Sentence Embedding基线方法)

文献阅读笔记 # Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

OVRL-V2: A simple state-of-art baseline for IMAGENAV and OBJECTNAV 论文阅读

文献阅读笔记 # Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation

论文笔记——FairMOT：A Simple Baseline for Multi-Object Tracking

【论文阅读】Topical Word Embeddings

Deep Fragment Embeddings for Bidirectional Image Sentence Mapping

SCD Self-Contrastive Decorrelation for Sentence Embeddings

SGPT: GPT Sentence Embeddings for Semantic Search

Complex Embeddings for Simple Link Prediction

论文阅读-Baseline与Benchmark介绍

论文阅读 DEFT: Detection Embeddings for Tracking

论文笔记Baseline Needs More Love:On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

【论文翻译】A simple yet effective baseline for 3d human pose estimation

Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Seg论文复现

『论文阅读』：Convolutional Neural Networks for Sentence Classification

[论文阅读笔记68]Sentence-BERT

【论文阅读】Realistic Datasets and A Strong Baseline

论文阅读笔记：《Contextual String Embeddings for Sequence Labeling》

【论文阅读】A Correlated Topic Model Using Word Embeddings

An Empirical Study on Leveraging Position Embeddings for TOWE 论文阅读笔记

【论文】A neural attention model for abstractive sentence summarization 阅读笔记

2019论文阅读3:Actor and Action Video Segmentation from a Sentence

《Conditional Network Embeddings》论文分析

论文阅读：A New Meta-Baseline for Few-Shot Learning

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