Papers Conditional Text Generation
“Conditional Text Generation” 태그가 달린 논문 71편 · 필터 해제
EEL: Efficiently Encoding Lattices for Reranking
Standard decoding approaches for conditional text generation tasks typically search for an output hypothesis with high model probability, but this may not yield the best hypothesis according to human judgments of quality…
Conditional Text GenerationRerankingText GenerationDiffuSIA: A Spiral Interaction Architecture for Encoder-Decoder Text Diffusion
Diffusion models have emerged as the new state-of-the-art family of deep generative models, and their promising potentials for text generation have recently attracted increasing attention. Existing studies mostly adopt a…
Conditional Text GenerationDecoderDialogue Generationmultimodal generation+4GlyphDiffusion: Text Generation as Image Generation
Diffusion models have become a new generative paradigm for text generation. Considering the discrete categorical nature of text, in this paper, we propose GlyphDiffusion, a novel diffusion approach for text generation vi…
Conditional Text GenerationDiversityGlyph Image GenerationImage Generation+2VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
In this paper, we propose a Vision-Audio-Language Omni-peRception pretraining model (VALOR) for multi-modal understanding and generation. Different from widely-studied vision-language pretraining models, VALOR jointly mo…
Audio captioningAudio-Video Question Answering (AVQA)Audio-Visual CaptioningAudio-visual Question Answering+16Input-length-shortening and text generation via attention values
Identifying words that impact a task's performance more than others is a challenge in natural language processing. Transformers models have recently addressed this issue by incorporating an attention mechanism that assig…
Conditional Text Generationtext-classificationText ClassificationText GenerationGENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation
We introduce GENIUS: a conditional text generation model using sketches as input, which can fill in the missing contexts for a given sketch (key information consisting of textual spans, phrases, or words, concatenated by…
Conditional Text GenerationData AugmentationLanguage ModelingLanguage Modelling+10Reward Gaming in Conditional Text Generation
To align conditional text generation model outputs with desired behaviors, there has been an increasing focus on training the model using reinforcement learning (RL) with reward functions learned from human annotations. …
Conditional Text GenerationReinforcement Learning (RL)Text GenerationFAST: Improving Controllability for Text Generation with Feedback Aware Self-Training
Controllable text generation systems often leverage control codes to direct various properties of the output like style and length. Inspired by recent work on causal inference for NLP, this paper reveals a previously ove…
AttributeCausal InferenceConditional Text Generationcounterfactual+1Demonstrating EMMA: Embodied MultiModal Agent for Language-guided Action Execution in 3D Simulated Environments
We demonstrate EMMA, an embodied multimodal agent which has been developed for the Alexa Prize SimBot challenge. The agent acts within a 3D simulated environment for household tasks. EMMA is a unified and multimodal gene…
Conditional Text GenerationText GenerationThe Dialog Must Go On: Improving Visual Dialog via Generative Self-Training
Visual dialog (VisDial) is a task of answering a sequence of questions grounded in an image, using the dialog history as context. Prior work has trained the dialog agents solely on VisDial data via supervised learning or…
Conditional Text GenerationOut-of-Distribution DetectionText GenerationVisual DialogBanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla
This work presents BanglaNLG, a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language. We aggregate six challenging conditional text generati…
Conditional Text GenerationDialogue GenerationLanguage ModelingLanguage Modelling+1AdaVAE: Exploring Adaptive GPT-2s in Variational Auto-Encoders for Language Modeling
Variational Auto-Encoder (VAE) has become the de-facto learning paradigm in achieving representation learning and generation for natural language at the same time. Nevertheless, existing VAE-based language models either …
Conditional Text GenerationDecoderLanguage ModelingLanguage Modelling+2Regression Transformer: Concurrent sequence regression and generation for molecular language modeling
Despite significant progress of generative models in the natural sciences, their controllability remains challenging. One fundamentally missing aspect of molecular or protein generative models is an inductive bias that c…
Conditional Text GenerationInductive BiasLanguage ModelingLanguage Modelling+3Discourse-Aware Prompt Design for Text Generation
Current efficient fine-tuning methods (e.g., adapters, prefix-tuning, etc.) have optimized conditional text generation via training a small set of extra parameters of the neural language model, while freezing the rest fo…
BlockingConditional Text GenerationLanguage ModellingText GenerationOn the Anatomy of Latent-variable Generative Models for Conditional Text Generation
Conditional text generation is a non-trivial task, which is until now predominantly performed with latent-variable generative models. In this work, we intend to explore several choices that are shown to affect the two es…
AnatomyConditional Text GenerationText GenerationDiscourse-Aware Soft Prompting for Text Generation
Current efficient fine-tuning methods (e.g., adapters, prefix-tuning, etc.) have optimized conditional text generation via training a small set of extra parameters of the neural language model, while freezing the rest fo…
BlockingConditional Text GenerationLanguage ModelingLanguage Modelling+1Realistic simulation of users for IT systems in cyber ranges
Generating user activity is a key capability for both evaluating security monitoring tools as well as improving the credibility of attacker analysis platforms (e.g., honeynets). In this paper, to generate this activity, …
Conditional Text GenerationText GenerationBag-of-Vectors Autoencoders for Unsupervised Conditional Text Generation
Text autoencoders are often used for unsupervised conditional text generation by applying mappings in the latent space to change attributes to the desired values. Recently, Mai et al. (2020) proposed Emb2Emb, a method to…
Conditional Text GenerationSentence SummarizationText GenerationExploring Conditional Text Generation for Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) is an NLP task that entails processing user-generated reviews to determine (i) the target being evaluated, (ii) the aspect category to which it belongs, and (iii) the sentiment expr…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Conditional Text GenerationSentiment Analysis+1Guided Generation of Cause and Effect
We present a conditional text generation framework that posits sentential expressions of possible causes and effects. This framework depends on two novel resources we develop in the course of this work: a very large-scal…
Conditional Text GenerationKnowledge GraphsText Generation