Papers Text Style Transfer
“Text Style Transfer” 태그가 달린 논문 199편 · 필터 해제
StyleShield: Exposing the Fragility of AIGC Detectors through Continuous Controllable Style Transfer
AI-generated content (AIGC) detectors are increasingly deployed in high-stakes settings such as academic integrity screening, yet their reliability rests on a fundamental paradox: as language models are trained on human-…
Text Style TransferSemantic SimilarityContinuous ControlText Style Transfer with Machine Translation for Graphic Designs
Globalization of graphic designs such as those used in marketing materials and magazines is increasingly important for communication to broad audiences. To accomplish this, the textual content in the graphic designs need…
Text Style TransferMachine TranslationWord AlignmentPlease Make it Sound like Human: Encoder-Decoder vs. Decoder-Only Transformers for AI-to-Human Text Style Transfer
AI-generated text has become common in academic and professional writing, prompting research into detection methods. Less studied is the reverse: systematically rewriting AI-generated prose to read as genuinely human-aut…
Text Style TransferText Style Transfer with Parameter-efficient LLM Finetuning and Round-trip Translation
This paper proposes a novel method for Text Style Transfer (TST) based on parameter-efficient fine-tuning of Large Language Models (LLMs). Addressing the scarcity of parallel corpora that map between styles, the study em…
parameter-efficient fine-tuningText Style TransferText Detoxification in isiXhosa and Yorùbá: A Cross-Lingual Machine Learning Approach for Low-Resource African Languages
Toxic language is one of the major barrier to safe online participation, yet robust mitigation tools are scarce for African languages. This study addresses this critical gap by investigating automatic text detoxification…
Interpretable Machine LearningText Style TransferUnsupervised Text Style Transfer for Controllable Intensity
Unsupervised Text Style Transfer (UTST) aims to build a system to transfer the stylistic properties of a given text without parallel text pairs. Compared with text transfer between style polarities, UTST for controllable…
Text Style TransferUTDesign: 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 TransferSceneTextStylizer: A Training-Free Scene Text Style Transfer Framework with Diffusion Model
With the rapid development of diffusion models, style transfer has made remarkable progress. However, flexible and localized style editing for scene text remains an unsolved challenge. Although existing scene text editin…
Text Style TransferRetrieval-Augmented Review Generation for Poisoning Recommender Systems
Recent studies have shown that recommender systems (RSs) are highly vulnerable to data poisoning attacks, where malicious actors inject fake user profiles, including a group of well-designed fake ratings, to manipulate r…
Text Style TransferImproving Text Style Transfer using Masked Diffusion Language Models with Inference-time Scaling
Masked diffusion language models (MDMs) have recently gained traction as a viable generative framework for natural language. This can be attributed to its scalability and ease of training compared to other diffusion mode…
Text Style TransferLearning Text Styles: A Study on Transfer, Attribution, and Verification
This thesis advances the computational understanding and manipulation of text styles through three interconnected pillars: (1) Text Style Transfer (TST), which alters stylistic properties (e.g., sentiment, formality) whi…
Text Style TransferEvaluating Text Style Transfer: A Nine-Language Benchmark for Text Detoxification
Despite notable advances in large language models (LLMs), reliable evaluation of text generation tasks such as text style transfer (TST) remains an open challenge. Existing research has shown that automatic metrics often…
Text Style TransferMachine TranslationText GenerationWETBench: A Benchmark for Detecting Task-Specific Machine-Generated Text on Wikipedia
Given Wikipedia's role as a trusted source of high-quality, reliable content, concerns are growing about the proliferation of low-quality machine-generated text (MGT) produced by large language models (LLMs) on its platf…
Text Style TransferImplementing Long Text Style Transfer with LLMs through Dual-Layered Sentence and Paragraph Structure Extraction and Mapping
This paper addresses the challenge in long-text style transfer using zero-shot learning of large language models (LLMs), proposing a hierarchical framework that combines sentence-level stylistic adaptation with paragraph…
SentenceStyle TransferText Style TransferZero-Shot LearningEvaluating Text Style Transfer Evaluation: Are There Any Reliable Metrics?
Text Style Transfer (TST) is the task of transforming a text to reflect a particular style while preserving its original content. Evaluating TST outputs is a multidimensional challenge, requiring the assessment of style …
Machine TranslationStyle TransferText Style TransferPredicting Compact Phrasal Rewrites with Large Language Models for ASR Post Editing
Large Language Models (LLMs) excel at rewriting tasks such as text style transfer and grammatical error correction. While there is considerable overlap between the inputs and outputs in these tasks, the decoding cost sti…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Grammatical Error CorrectionMachine Translation+4Multi-Attribute Constraint Satisfaction via Language Model Rewriting
Obeying precise constraints on top of multiple external attributes is a common computational problem underlying seemingly different domains, from controlled text generation to protein engineering. Existing language model…
AttributeLanguage ModelingLanguage Modellingmodel+4Multilingual and Explainable Text Detoxification with Parallel Corpora
Even with various regulations in place across countries and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022, digital abusive speech remains a significant iss…
DescriptiveStyle TransferText Style TransferStyle-Specific Neurons for Steering LLMs in Text Style Transfer
Text style transfer (TST) aims to modify the style of a text without altering its original meaning. Large language models (LLMs) demonstrate superior performance across multiple tasks, including TST. However, in zero-sho…
DiversityStyle TransferText Style TransferWAS: Dataset and Methods for Artistic Text Segmentation
Accurate text segmentation results are crucial for text-related generative tasks, such as text image generation, text editing, text removal, and text style transfer. Recently, some scene text segmentation methods have ma…
DecoderDiversityImage GenerationSegmentation+3