Papers Text Segmentation
“Text Segmentation” 태그가 달린 논문 124편 · 필터 해제
Proofread: Fixes All Errors with One Tap
The impressive capabilities in Large Language Models (LLMs) provide a powerful approach to reimagine users' typing experience. This paper demonstrates Proofread, a novel Gboard feature powered by a server-side LLM in Gbo…
AllQuantizationReinforcement Learning (RL)Sentence+1Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering
In customer service technical support, swiftly and accurately retrieving relevant past issues is critical for efficiently resolving customer inquiries. The conventional retrieval methods in retrieval-augmented generation…
Knowledge GraphsQuestion AnsweringRAGRetrieval+3Detecting AI-Generated Sentences in Human-AI Collaborative Hybrid Texts: Challenges, Strategies, and Insights
This study explores the challenge of sentence-level AI-generated text detection within human-AI collaborative hybrid texts. Existing studies of AI-generated text detection for hybrid texts often rely on synthetic dataset…
Boundary DetectionSentenceSentence ClassificationText Detection+1From Text Segmentation to Smart Chaptering: A Novel Benchmark for Structuring Video Transcriptions
Text segmentation is a fundamental task in natural language processing, where documents are split into contiguous sections. However, prior research in this area has been constrained by limited datasets, which are either …
Headline GenerationSegmentationText SegmentationHi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation
The Segment Anything Model (SAM), a profound vision foundation model pretrained on a large-scale dataset, breaks the boundaries of general segmentation and sparks various downstream applications. This paper introduces Hi…
Hierarchical Text Segmentationparameter-efficient fine-tuningSegmentationText SegmentationA Reliable Knowledge Processing Framework for Combustion Science using Foundation Models
This research explores the integration of large language models (LLMs) into scientific data assimilation, focusing on combustion science as a case study. Leveraging foundational models integrated with Retrieval-Augmented…
ArticlesPrompt EngineeringRAGRetrieval-augmented Generation+1Segmenting Messy Text: Detecting Boundaries in Text Derived from Historical Newspaper Images
Text segmentation, the task of dividing a document into sections, is often a prerequisite for performing additional natural language processing tasks. Existing text segmentation methods have typically been developed and …
Optical Character RecognitionSegmentationText SegmentationUPOCR: Towards Unified Pixel-Level OCR Interface
In recent years, the optical character recognition (OCR) field has been proliferating with plentiful cutting-edge approaches for a wide spectrum of tasks. However, these approaches are task-specifically designed with div…
DecoderOptical Character RecognitionOptical Character Recognition (OCR)Text Detection+1Curved Diffusion: A Generative Model With Optical Geometry Control
State-of-the-art diffusion models can generate highly realistic images based on various conditioning like text, segmentation, and depth. However, an essential aspect often overlooked is the specific camera geometry used …
Text SegmentationFiltered Semi-Markov CRF
Semi-Markov CRF has been proposed as an alternative to the traditional Linear Chain CRF for text segmentation tasks such as Named Entity Recognition (NER). Unlike CRF, which treats text segmentation as token-level predic…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+2Self-supervised Scene Text Segmentation with Object-centric Layered Representations Augmented by Text Regions
Text segmentation tasks have a very wide range of application values, such as image editing, style transfer, watermark removal, etc.However, existing public datasets are of poor quality of pixel-level labels that have be…
SegmentationStyle TransferText SegmentationA Comparative Study of Sentence Embedding Models for Assessing Semantic Variation
Analyzing the pattern of semantic variation in long real-world texts such as books or transcripts is interesting from the stylistic, cognitive, and linguistic perspectives. It is also useful for applications such as text…
Document SummarizationSemantic SimilaritySemantic Textual SimilaritySentence+5Handwritten and Printed Text Segmentation: A Signature Case Study
While analyzing scanned documents, handwritten text can overlap with printed text. This overlap causes difficulties during the optical character recognition (OCR) and digitization process of documents, and subsequently, …
Binary ClassificationOptical Character RecognitionOptical Character Recognition (OCR)Segmentation+1PSSTRNet: Progressive Segmentation-guided Scene Text Removal Network
Scene text removal (STR) is a challenging task due to the complex text fonts, colors, sizes, and background textures in scene images. However, most previous methods learn both text location and background inpainting impl…
DecoderSegmentationText SegmentationExpanding Scope: Adapting English Adversarial Attacks to Chinese
Recent studies have revealed that NLP predictive models are vulnerable to adversarial attacks. Most existing studies focused on designing attacks to evaluate the robustness of NLP models in the English language alone. Li…
Adversarial AttackAdversarial RobustnessText SegmentationCCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image Binarization
To efficiently extract textual information from color degraded document images is a significant research area. The prolonged imperfect preservation of ancient documents has led to various types of degradation, such as pa…
BinarizationImage EnhancementSemantic SegmentationText SegmentationWeakly-Supervised Text Instance Segmentation
Text segmentation is a challenging vision task with many downstream applications. Current text segmentation methods require pixel-level annotations, which are expensive in the cost of human labor and limited in applicati…
Contrastive LearningInstance SegmentationSegmentationSemantic Segmentation+3Document Summarization with Text Segmentation
In this paper, we exploit the innate document segment structure for improving the extractive summarization task. We build two text segmentation models and find the most optimal strategy to introduce their output predicti…
ArticlesDocument SummarizationExtractive SummarizationSegmentation+2Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks
The efficient extraction of text information from the background in degraded color document images is an important challenge in the preservation of ancient manuscripts. The imperfect preservation of ancient manuscripts h…
AvgBinarizationImage EnhancementSemantic Segmentation+1DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding
In this paper, we study the problem of visual grounding by considering both phrase extraction and grounding (PEG). In contrast to the previous phrase-known-at-test setting, PEG requires a model to extract phrases from te…
object-detectionObject DetectionPhrase Extraction and Grounding (PEG)Phrase Grounding+3