Papers Conditional Text Generation
“Conditional Text Generation” 태그가 달린 논문 71편 · 필터 해제
UTDesign: A Unified Framework for Stylized Text Editing and Generation in Graphic Design Images
AI-assisted graphic design has emerged as a powerful tool for automating the creation and editing of design elements such as posters, banners, and advertisements. While diffusion-based text-to-image models have demonstra…
Conditional Text GenerationText Style TransferACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control
Generating high-quality synthetic text under differential privacy (DP) is critical for training and evaluating language models without compromising user privacy. Prior work on synthesizing DP datasets often fail to prese…
Conditional Text GenerationGenerating Surface for Text-to-3D using 2D Gaussian Splatting
Recent advancements in Text-to-3D modeling have shown significant potential for the creation of 3D content. However, due to the complex geometric shapes of objects in the natural world, generating 3D content remains a ch…
Conditional Text GenerationSyntax-Guided Diffusion Language Models with User-Integrated Personalization
Large language models have made revolutionary progress in generating human-like text, yet their outputs often tend to be generic, exhibiting insufficient structural diversity, which limits personalized expression. Recent…
Conditional Text GenerationCtrlDiff: Boosting Large Diffusion Language Models with Dynamic Block Prediction and Controllable Generation
Although autoregressive models have dominated language modeling in recent years, there has been a growing interest in exploring alternative paradigms to the conventional next-token prediction framework. Diffusion-based l…
Conditional Text GenerationLanguage ModelingLanguage ModellingText GenerationSCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation
Large Language Models (LLMs), when used for conditional text generation, often produce hallucinations, i.e., information that is unfaithful or not grounded in the input context. This issue arises in typical conditional t…
Conditional Text GenerationData-to-Text GenerationText GenerationText SummarizationMOPO: Multi-Objective Prompt Optimization for Affective Text Generation
How emotions are expressed depends on the context and domain. On X (formerly Twitter), for instance, an author might simply use the hashtag #anger, while in a news headline, emotions are typically written in a more polit…
Conditional Text GenerationText GenerationDiscrete Copula Diffusion
Discrete diffusion models have recently shown significant progress in modeling complex data, such as natural languages and DNA sequences. However, unlike diffusion models for continuous data, which can generate high-qual…
Conditional Text GenerationDenoisingText GenerationEvaluation of Language Models in the Medical Context Under Resource-Constrained Settings
Since the Transformer architecture emerged, language model development has grown, driven by their promising potential. Releasing these models into production requires properly understanding their behavior, particularly i…
Conditional Text GenerationLanguage Modellingtext-classificationText Classification+2TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings
This paper presents the Text Encoding Diffusion Model (TEncDM), a novel approach to diffusion modeling that operates in the space of pre-trained language model encodings. In contrast to traditionally used embeddings, enc…
Conditional Text GenerationDecoderDenoisingLanguage Modeling+4LOCOST: State-Space Models for Long Document Abstractive Summarization
State-space models are a low-complexity alternative to transformers for encoding long sequences and capturing long-term dependencies. We propose LOCOST: an encoder-decoder architecture based on state-space models for con…
Abstractive Text SummarizationBook summarizationConditional Text GenerationDecoder+2Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI Models
Recent studies of the emergent capabilities of transformer-based Natural Language Understanding (NLU) models have indicated that they have an understanding of lexical and compositional semantics. We provide evidence that…
Conditional Text GenerationNatural Language InferenceNatural Language UnderstandingSensitivity+1IPAD: Iterative, Parallel, and Diffusion-based Network for Scene Text Recognition
Nowadays, scene text recognition has attracted more and more attention due to its diverse applications. Most state-of-the-art methods adopt an encoder-decoder framework with the attention mechanism, autoregressively gene…
Conditional Text GenerationDecoderLanguage ModelingLanguage Modelling+2MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning capacities, the resulting models are ei…
ArticlesConditional Text GenerationFew-Shot LearningMultiple Choice Question Answering (MCQA)+2Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation
Large Language Models (LLMs) can generate biased and toxic responses. Yet most prior work on LLM gender bias evaluation requires predefined gender-related phrases or gender stereotypes, which are challenging to be compre…
Conditional Text GenerationFairnessText GenerationEmotion-Conditioned Text Generation through Automatic Prompt Optimization
Conditional natural language generation methods often require either expensive fine-tuning or training a large language model from scratch. Both are unlikely to lead to good results without a substantial amount of data a…
Conditional Text GenerationFew-Shot Text ClassificationLanguage ModelingLanguage Modelling+6Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark Remedy
To mitigate potential risks associated with language models, recent AI detection research proposes incorporating watermarks into machine-generated text through random vocabulary restrictions and utilizing this informatio…
Conditional Text GenerationData-to-Text GenerationText GenerationControllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation
Prompting large language models (LLMs) for data augmentation has recently become a common practice in few-shot NLP tasks. In this paper, we propose Chain-of-Thought Attribute Manipulation (CoTAM), a novel approach that g…
Aspect-Based Sentiment AnalysisAttributeConditional Text GenerationData Augmentation+8Learning to Generate Better Than Your LLM
Reinforcement learning (RL) has emerged as a powerful paradigm for fine-tuning Large Language Models (LLMs) for text generation. In particular, recent LLMs such as ChatGPT and GPT-4 can engage in fluent conversations wit…
Conditional Text Generationreinforcement-learningReinforcement Learning (RL)Text GenerationDiffuDetox: A Mixed Diffusion Model for Text Detoxification
Text detoxification is a conditional text generation task aiming to remove offensive content from toxic text. It is highly useful for online forums and social media, where offensive content is frequently encountered. Int…
Conditional Text GenerationDiversitymodelText Generation