Papers Conditional Text Generation
“Conditional Text Generation” 태그가 달린 논문 71편 · 필터 해제
Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders
Conditional Text Generation has drawn much attention as a topic of Natural Language Generation (NLG) which provides the possibility for humans to control the properties of generated contents. Current conditional generati…
Conditional Text GenerationDiversityText GenerationImproved Variational Neural Machine Translation by Promoting Mutual Information
Posterior collapse plagues VAEs for text, especially for conditional text generation with strong autoregressive decoders. In this work, we address this problem in variational neural machine translation by explicitly prom…
Conditional Text GenerationDecoderMachine TranslationText Generation+1Transfer Reward Learning for Policy Gradient-Based Text Generation
Task-specific scores are often used to optimize for and evaluate the performance of conditional text generation systems. However, such scores are non-differentiable and cannot be used in the standard supervised learning …
Conditional Text GenerationImage CaptioningPolicy Gradient MethodsSemantic Similarity+4Conditional Text Generation for Harmonious Human-Machine Interaction
In recent years, with the development of deep learning, text generation technology has undergone great changes and provided many kinds of services for human beings, such as restaurant reservation and daily communication.…
Conditional Text GenerationText GenerationEncoder-Agnostic Adaptation for Conditional Language Generation
Large pretrained language models have changed the way researchers approach discriminative natural language understanding tasks, leading to the dominance of approaches that adapt a pretrained model for arbitrary downstrea…
Conditional Text GenerationLanguage ModelingLanguage ModellingNatural Language Understanding+2Topic-Guided Variational Auto-Encoder for Text Generation
We propose a topic-guided variational auto-encoder (TGVAE) model for text generation. Distinct from existing variational auto-encoder (VAE) based approaches, which assume a simple Gaussian prior for latent code, our mode…
Conditional Text GenerationText GenerationPretraining for Conditional Generation with Pseudo Self Attention
Large pretrained language representation models have changed the way researchers approach discriminative natural language understanding tasks, leading to the dominance of approaches that finetune a pretrained model. Howe…
Conditional Text GenerationNatural Language UnderstandingText GenerationTransfer LearningPragmatically Informative Text Generation
We improve the informativeness of models for conditional text generation using techniques from computational pragmatics. These techniques formulate language production as a game between speakers and listeners, in which a…
Abstractive Text SummarizationConditional Text GenerationData-to-Text GenerationGrounded language learning+2Topic-Guided Variational Autoencoders for Text Generation
We propose a topic-guided variational autoencoder (TGVAE) model for text generation. Distinct from existing variational autoencoder (VAE) based approaches, which assume a simple Gaussian prior for the latent code, our mo…
Conditional Text GenerationText GenerationConditional Variational Autoencoder for Neural Machine Translation
We explore the performance of latent variable models for conditional text generation in the context of neural machine translation (NMT). Similar to Zhang et al., we augment the encoder-decoder NMT paradigm by introducing…
Conditional Text GenerationDecoderMachine TranslationNMT+2Generating Text through Adversarial Training using Skip-Thought Vectors
GANs have been shown to perform exceedingly well on tasks pertaining to image generation and style transfer. In the field of language modelling, word embeddings such as GLoVe and word2vec are state-of-the-art methods for…
Conditional Text GenerationLanguage ModellingSentenceSentence Embeddings+3