Papers Boundary Detection
“Boundary Detection” 태그가 달린 논문 404편 · 필터 해제
Computational Measurement of Team-Process Phase Dynamics in Collaborative Virtual Reality
Collaborative virtual reality (VR) environments make team communication observable as it unfolds, but conventional transcript analyses often summarize entire trials or divide them into fixed temporal windows. Such approa…
Boundary DetectionLycheeMemory V2: Efficient Long-Term Memory for LLM Agents via Semantic Segment-Level Consolidation
Long-horizon LLM agents must preserve information from past interactions to support future tasks. Existing memory systems typically rely on eager consolidation, invoking LLMs after each interaction to extract, summarize,…
Boundary DetectionEvaluation of forced alignment of code-mixed speech: the case of Hindi-English
Code-mixed speech poses unique challenges to forced alignment: expanded inventories, orthographic errors, and speaker variation. We evaluate forced alignment of Hindi-English code-mixed speech using the Montreal Forced A…
Boundary DetectionWGDnet: Wishart-guided Geometric-aware Deep Network for PolSAR Image Classification
Polarimetric Synthetic Aperture Radar (PolSAR) classification underpins all-weather Earth observation. Conventional Wishart methods depend on rigid handcrafted operators with limited adaptability, while mainstream deep n…
Image ClassificationBoundary DetectionFSB-Net: Frequency-Spatial Boundary Network for Brain Stroke Lesion Segmentation in Non-Contrast CT
Accurate segmentation of brain stroke lesions in non-contrast computed tomography (NCCT) scans is critical for rapid clinical decision-making, yet remains difficult due to the low contrast between lesion and normal brain…
Lesion SegmentationBoundary DetectionSpeaker-Disentangled Chunk-Wise Regression for Syllabic Tokenization
Unsupervised syllabic tokenization aims to learn discrete syllabic tokens that capture latent linguistic content-related structure from raw speech. Recent syllabic tokenization methods employ teacher-student distillation…
Boundary DetectionSUNTA: Hierarchical Video Prediction with Surprise-based Chunking
Hierarchical state-space models (HSSMs) offer a promising approach to long-horizon prediction by segmenting sequences into temporal chunks. However, their performance hinges on how chunk boundaries are determined. While …
Boundary DetectionVideo PredictionFully Differentiable Neural Forced Alignment via Soft Dynamic Programming
Recent advances in sequence modeling have significantly improved ASR systems, bringing them close to human-level recognition accuracy and enhancing robustness across diverse acoustic conditions and languages. In contrast…
Boundary DetectionReflectiChain: Epistemic Grounding in LLM-Driven World Models for Supply Chain Resilience
AI agents in supply chains face a fundamental epistemic gap: large language models (LLMs) interpret policies but lack physical grounding, while reinforcement learning (RL) optimizes flows but is semantically blind to uns…
Reinforcement LearningBoundary DetectionRate-optimal neural boundary detection from unlabeled noisy images
We study boundary detection for unlabeled noisy images from a statistical perspective. The aim is to recover an unknown object region from raw intensity observations without pixel-wise annotating labels or a parametric m…
Boundary DetectionClinicalEncoder26AM: A Multlilingual Diagnosable ColBERT Model; Evidences from the MultiClinNER Shared Task
ClinicalEncoder26AM is a multilingual Diagnosable ColBERT for clinical and biomedical texts, which aligns at multiple levels its token-level semantic with ClinicalMap25, a clinical latent space inspired by BioLORD-2023 a…
Information ExtractionBoundary DetectionThe Concept Allocation Zone: Tracking How Concepts Form Across Transformer Depth
Concept formation in transformer language models is a depth-extended process, not a single-layer event: a concept becomes separable across one or more contiguous regions of the residual stream - its Concept Allocation Zo…
Boundary DetectionPRISM: Perinuclear Ring-based Image Segmentation Method for Acute Lymphoblastic Leukemia Classification
Automated analysis of peripheral blood smears for Acute Lymphoblastic Leukemia (ALL) is hindered by low contrast and substantial variability in cytoplasmic appearance, which complicate conventional membrane-based segment…
Boundary DetectionImage SegmentationA Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning
Accurate boundary detection in high-dimensional data remains a central challenge in unsupervised learning, particularly in the presence of non-linear structures and heterogeneous densities. In this work, we introduce Mea…
Boundary DetectionTransVLM: A Vision-Language Framework and Benchmark for Detecting Any Shot Transitions
Traditional Shot Boundary Detection (SBD) inherently struggles with complex transitions by formulating the task around isolated cut points, frequently yielding corrupted video shots. We address this fundamental limitatio…
Boundary DetectionOmniShotCut: Holistic Relational Shot Boundary Detection with Shot-Query Transformer
Shot Boundary Detection (SBD) aims to automatically identify shot changes and divide a video into coherent shots. While SBD was widely studied in the literature, existing methods often produce non-interpretable boundarie…
Boundary DetectionHiCrew: Hierarchical Reasoning for Long-Form Video Understanding via Question-Aware Multi-Agent Collaboration
Long-form video understanding remains fundamentally challenged by pervasive spatiotemporal redundancy and intricate narrative dependencies that span extended temporal horizons. While recent structured representations com…
Boundary DetectionExploring Boundary-Aware Spatial-Frequency Fusion for Camouflaged Object Detection
Camouflaged Object Detection is challenging due to the high degree of similarity between camouflaged objects and their surrounding backgrounds. Current COD methods mainly rely on edge extraction in the spatial domain and…
Boundary DetectionObject DetectionCan We Trust a Black-box LLM? LLM Untrustworthy Boundary Detection via Bias-Diffusion and Multi-Agent Reinforcement Learning
Large Language Models (LLMs) have shown a high capability in answering questions on a diverse range of topics. However, these models sometimes produce biased, ideologized or incorrect responses, limiting their applicatio…
Multi-agent Reinforcement LearningBoundary DetectionGeneral KnowledgePredict, Don't React: Value-Based Safety Forecasting for LLM Streaming
In many practical LLM deployments, a single guardrail is used for both prompt and response moderation. Prompt moderation operates on fully observed text, whereas streaming response moderation requires safety decisions to…
Boundary Detection