Browse > Methodology > Transfer Learning > Multi-Task Learning

Multi-Task Learning

141 papers with code · Methodology
Subtask of Transfer Learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

State-of-the-art leaderboards

Greatest papers with code

Semi-Supervised Sequence Modeling with Cross-View Training

EMNLP 2018 tensorflow/models

We therefore propose Cross-View Training (CVT), a semi-supervised learning algorithm that improves the representations of a Bi-LSTM sentence encoder using a mix of labeled and unlabeled data.

CCG SUPERTAGGING DEPENDENCY PARSING MACHINE TRANSLATION MULTI-TASK LEARNING NAMED ENTITY RECOGNITION UNSUPERVISED REPRESENTATION LEARNING

DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks

13 Mar 2017tensorflow/models

In this work, we present a compact, modular framework for constructing novel recurrent neural architectures.

DEPENDENCY PARSING MULTI-TASK LEARNING

One Model To Learn Them All

16 Jun 2017tensorflow/tensor2tensor

We present a single model that yields good results on a number of problems spanning multiple domains.

IMAGE CAPTIONING IMAGE CLASSIFICATION MULTI-TASK LEARNING

ERNIE 2.0: A Continual Pre-training Framework for Language Understanding

29 Jul 2019PaddlePaddle/ERNIE

Recently, pre-trained models have achieved state-of-the-art results in various language understanding tasks, which indicates that pre-training on large-scale corpora may play a crucial role in natural language processing.

LINGUISTIC ACCEPTABILITY MULTI-TASK LEARNING NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC TEXTUAL SIMILARITY SENTIMENT ANALYSIS

Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning

ICLR 2018 facebookresearch/InferSent

In this work, we present a simple, effective multi-task learning framework for sentence representations that combines the inductive biases of diverse training objectives in a single model.

MULTI-TASK LEARNING NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION SEMANTIC TEXTUAL SIMILARITY

Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding

20 Apr 2019namisan/mt-dnn

This paper explores the use of knowledge distillation to improve a Multi-Task Deep Neural Network (MT-DNN) (Liu et al., 2019) for learning text representations across multiple natural language understanding tasks.

MULTI-TASK LEARNING

A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks

14 Nov 2018huggingface/hmtl

The model is trained in a hierarchical fashion to introduce an inductive bias by supervising a set of low level tasks at the bottom layers of the model and more complex tasks at the top layers of the model.

MULTI-TASK LEARNING NAMED ENTITY RECOGNITION RELATION EXTRACTION

Agnostic Lane Detection

2 May 2019cardwing/Codes-for-Lane-Detection

Lane detection is an important yet challenging task in autonomous driving, which is affected by many factors, e. g., light conditions, occlusions caused by other vehicles, irrelevant markings on the road and the inherent long and thin property of lanes.

AUTONOMOUS DRIVING INSTANCE SEGMENTATION LANE DETECTION MULTI-TASK LEARNING SEMANTIC SEGMENTATION

OmniNet: A unified architecture for multi-modal multi-task learning

17 Jul 2019subho406/OmniNet

We propose a spatio-temporal cache mechanism that enables learning spatial dimension of the input in addition to the hidden states corresponding to the temporal input sequence.

IMAGE CAPTIONING MULTI-TASK LEARNING PART-OF-SPEECH TAGGING QUESTION ANSWERING VISUAL QUESTION ANSWERING