Автокодировщик
Related Papers
It’s Not You, it’s Me: Detecting Flirting and its Misperception in Speed-Dates
Automatically detecting human social in- tentions from spoken conversation is an important task for dialogue understand- ing. Since the social intentions of the speaker may differ from what is perceived …...
Adversarial Decomposition of Text Representation
AbstractIn this paper, we present a method for adversarial decomposition of text representation. This method can be used to decompose a representation of an input sentence into several independent vectors, …...
Ranking-Based Autoencoder for Extreme Multi-label Classification
AbstractExtreme Multi-label classification (XML) is an important yet challenging machine learning task, that assigns to each instance its most relevant candidate labels from an extremely large label collection, where the …...
A Neural Model for Aggregating Coreference Annotation in Crowdsourcing
AbstractCoreference resolution is the task of identifying all mentions in a text that refer to the same real-world entity. Collecting sufficient labelled data from expert annotators to train a high-performance …...
CMCE at SemEval-2020 Task 1: Clustering on Manifolds of Contextualized Embeddings to Detect Historical Meaning Shifts
AbstractThis paper describes the system Clustering on Manifolds of Contextualized Embeddings (CMCE) submitted to the SemEval-2020 Task 1 on Unsupervised Lexical Semantic Change Detection. Subtask 1 asks to identify whether …...
A Distributional Lens for Multi-Aspect Controllable Text Generation
AbstractMulti-aspect controllable text generation is a more challenging and practical task than single-aspect control. Existing methods achieve complex multi-aspect control by fusing multiple controllers learned from single-aspect, but suffer from …...
Towards Robust and Semantically Organised Latent Representations for Unsupervised Text Style Transfer
AbstractRecent studies show that auto-encoder based approaches successfully perform language generation, smooth sentence interpolation, and style transfer over unseen attributes using unlabelled datasets in a zero-shot manner. The latent space …...
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models
AbstractRecent transformer language models achieve outstanding results in many natural language processing (NLP) tasks. However, their enormous size often makes them impractical on memory-constrained devices, requiring practitioners to compress them …...