223 Open source projects that are alternatives of or similar to Transferable-E2E-ABSA

Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification (AAAI'19)

Aspect Based Sentiment Analysis is a special type of sentiment analysis. In an explicit aspect, opinion is expressed on a target(opinion target), this aspect-polarity extraction is known as ABSA.

Awesome Domain Adaptation Python Toolbox

Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

A collection of AWESOME things about domian adaptation

Code of Gradually Vanishing Bridge for Adversarial Domain Adaptation (CVPR2020)

Attending to Discriminative Certainty for Domain Adaptation

( CVPR2019 Oral ) Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation

Code and datasets for EMNLP2018 paper ‘‘Adaptive Semi-supervised Learning for Cross-domain Sentiment Classification’’.

Domain-Adversarial Neural Network in Tensorflow

No description or website provided.

CrossNER: Evaluating Cross-Domain Named Entity Recognition (AAAI-2021)

🌈 Implementation of Neural Network based Named Entity Recognizer (Lample+, 2016) using Chainer.

[CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation

[ICCV 2019 Oral] TA3N: https://github.com/cmhungsteve/TA3N (Most updated repo)

Hierarchically-Refined Label Attention Network for Sequence Labeling

Collateral Learning - Functional Encryption and Adversarial Training on partially encrypted networks

Sentiment Analysis with Deep Learning models. Implemented with Tensorflow and Keras.

A TensorFlow implementation of Neural Sequence Labeling model, which is able to tackle sequence labeling tasks such as POS Tagging, Chunking, NER, Punctuation Restoration and etc.

Macadam是一个以Tensorflow(Keras)和bert4keras为基础，专注于文本分类、序列标注和关系抽取的自然语言处理工具包。支持RANDOM、WORD2VEC、FASTTEXT、BERT、ALBERT、ROBERTA、NEZHA、XLNET、ELECTRA、GPT-2等EMBEDDING嵌入; 支持FineTune、FastText、TextCNN、CharCNN、BiRNN、RCNN、DCNN、CRNN、DeepMoji、SelfAttention、HAN、Capsule等文本分类算法; 支持CRF、Bi-LSTM-CRF、CNN-LSTM、DGCNN、Bi-LSTM-LAN、Lattice-LSTM-Batch、MRC等序列标注算法。

Implementation of Domain Adaption in One-Shot Learning

Helsinki Prosody Corpus and A System for Predicting Prosodic Prominence from Text

A (CNN+)RNN(LSTM/BiLSTM)+CRF model for sequence labelling.😏

Aspect extraction from product reviews - window-CNN+maxpool+CRF, BiLSTM+CRF, MLP+CRF

AISTATS 2019: Reference-based Adversarial Sampling & Its applications to Soft Q-learning

A HMM-like linear-chain CRF, used Tensorflow API. 🐣

A very simple framework for state-of-the-art Natural Language Processing (NLP)

[CVPR 2020] Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation (PyTorch)

Source code of our submission (Rank 1) for Multi-Source Domain Adaptation task in VisDA-2019

IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm

End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF implement in pyotrch

Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.

multi_task_NLP is a utility toolkit enabling NLP developers to easily train and infer a single model for multiple tasks.

code for our ECCV 2020 paper "A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation"

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

stylegan-nada.github.io/

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

Multichannel Semantic Segmentation with Unsupervised Domain Adaptation

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

Multimodal Adversarial Network for Cross-modal Retrieval (PyTorch Code)

Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017

Inference with state-of-the-art models (pre-trained by LD-Net / AutoNER / VanillaNER / ...)

Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.

Code for implementation of Unlearning Scanner Bias for MRI Harmonisation

Code and models for the paper " Position-Aware Tagging for Aspect Sentiment Triplet Extraction", EMNLP 2020.

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

Powerful unsupervised domain adaptation method for dense retrieval. Requires only unlabeled corpus and yields massive improvement: "GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval" https://arxiv.org/abs/2112.07577

reference pytorch code for named entity tagging

中文命名实体识别（包括多种模型：HMM，CRF，BiLSTM，BiLSTM+CRF的具体实现）

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem

Causality Extraction based on Self-Attentive BiLSTM-CRF with Transferred Embeddings

Empower Sequence Labeling with Task-Aware Language Model

Sequence Labeling in Tensorflow

Here is the code for the paper ``Aspect-Level Sentiment Analysis via Convolution over Dependency Tree'' accepted by EMNLP2019.

Implementation of paper Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa.

CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition

The classical BiLSTM-CRF model implemented in Tensorflow, for sequence labeling tasks. In Vex version, everything is configurable.

code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'

A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

A TensorFlow implementation of Recurrent Neural Networks for Sequence Classification and Sequence Labeling