Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, shape drawings, and mechanical engineering drawings.
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representative citing papers
PRISM-VO introduces photometric plenoptic bundle adjustment for drift-resilient, metric-scale visual odometry from a single focused plenoptic camera.
RESOLVE provides a controlled multi-resolution LiDAR and camera benchmark for evaluating 3D detection and tracking under point sparsity variations in roadside cooperative perception.
Sparse Context achieves 2-4x faster inference in reference-conditioned diffusion models by fine-tuning with random token dropping and applying task-aware selection at inference time, without loss of visual quality.
TIDES simulates realistic event camera streams in continuous time via dynamic Gaussian splatting with adaptive occlusion handling and sensor artifact modeling, claiming SOTA fidelity and better downstream transfer than prior methods.
A taxonomy of SNN training algorithms is presented with the release of NeuroTrain, an open benchmarking framework for reproducible comparisons across datasets and architectures.
LoopUS converts pretrained LLMs into looped latent refinement models via block decomposition, selective gating, random deep supervision, and confidence-based early exiting to improve reasoning performance.
The paper introduces the VODA setting for domain adaptation from scratch using vision-language models and presents TS-DRD, which achieves competitive performance on standard benchmarks without source models.
Introduces ViTextCaps dataset and PhonoSTFG phonological graph fusion framework for Vietnamese scene-text image captioning, showing cross-modal graph edges harm performance.
DSR is a neuro-symbolic autoformalization framework using operator trees that achieves new state-of-the-art results on the PRIME benchmark of 156 Lean 4 theorems.
Presents the ev-CIVIL dataset and benchmark showing that event-based cameras can support real-time detection of cracks and spalling in civil infrastructure under challenging lighting.
A Debye CZT-based wave-optics pipeline generates lens-diverse synthetic defocus blur datasets that improve cross-device deblurring generalization over existing real and synthetic data.
MIC casts diffusion motion generation as stochastic control to support both objective-based and criterion-based constraints without training or differentiability requirements.
CriterionSI infers clustering criteria from sequential user drags via LLMs to produce progressively aligned image cluster layouts.
SENTRY is a plug-and-play module that replaces confidence-based memory writes with neighbor-aware cycle-consistent validation in SAM2 trackers, yielding new zero-shot SOTA results on LaSOT, GOT-10k and other benchmarks.
Differential Unfolding replaces uniform stacking in deep unfolding networks with a heterogeneous structure of anchoring and differential evolution stages to achieve better accuracy-efficiency trade-offs in video SCI reconstruction.
A plug-and-play perceptual wrapper using common random noise and Wasserstein Distortion supervision improves texture quality and reduces model size in 3D Gaussian Splatting.
KITScenes Multimodal presents a new multimodal autonomous driving dataset with complete HD maps and four benchmarks for spatial learning tasks including online map construction and end-to-end driving.
Federated personalization of foundation models creates hard-to-detect trustworthiness failures due to privacy constraints, and existing benchmarks cannot adequately evaluate them.
RefDiffNet is a lightweight input enhancement block that uses reference image comparison to expose PCB defects, delivering up to 18% relative mAP50:95 gains across YOLO, RT-DETR, and Faster R-CNN detectors with 0.004-0.005M extra parameters.
Decomposed Vision-Language Alignment framework factorizes prompts into concept and attribute tokens with Feature-Gated Cross-Attention for better compositional generalization in fine-grained open-vocabulary segmentation.
MetaSR adaptively orchestrates metadata in a DiT-based generative SR model to deliver up to 1 dB PSNR gains and 50% bitrate savings across diverse content and degradations.
Hallucinations in multimodal reasoners cluster at high-entropy pivot tokens due to intermediate-layer visual anchoring failure, and V-STAR mitigates this with attention rewards plus forced reflection.
FMG-Pan is a model-guided instance-wise adaptation framework for real-world pansharpening that adds physical fidelity constraints to deliver state-of-the-art fusion quality with training and inference completed in seconds on single image pairs.
citing papers explorer
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A document is worth a structured record: Principled inductive bias design for document recognition
Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, shape drawings, and mechanical engineering drawings.
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PRISM-VO: Scale-Aware Visual Odometry Using Photometric Plenoptic Bundle Adjustment
PRISM-VO introduces photometric plenoptic bundle adjustment for drift-resilient, metric-scale visual odometry from a single focused plenoptic camera.
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RESOLVE: A Multi-Resolution and Multi-Modal Dataset for Roadside Cooperative Perception
RESOLVE provides a controlled multi-resolution LiDAR and camera benchmark for evaluating 3D detection and tracking under point sparsity variations in roadside cooperative perception.
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Keep The Essentials: Efficient Reference Conditioned Generation via Token Dropping
Sparse Context achieves 2-4x faster inference in reference-conditioned diffusion models by fine-tuning with random token dropping and applying task-aware selection at inference time, without loss of visual quality.
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TIDES: Time-Derivative Event Simulation via Deformable Reconstruction
TIDES simulates realistic event camera streams in continuous time via dynamic Gaussian splatting with adaptive occlusion handling and sensor artifact modeling, claiming SOTA fidelity and better downstream transfer than prior methods.
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NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework
A taxonomy of SNN training algorithms is presented with the release of NeuroTrain, an open benchmarking framework for reproducible comparisons across datasets and architectures.
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LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models
LoopUS converts pretrained LLMs into looped latent refinement models via block decomposition, selective gating, random deep supervision, and confidence-based early exiting to improve reasoning performance.
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Rethinking the Need for Source Models: Source-Free Domain Adaptation from Scratch Guided by a Vision-Language Model
The paper introduces the VODA setting for domain adaptation from scratch using vision-language models and presents TS-DRD, which achieves competitive performance on standard benchmarks without source models.
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Linguistically Informed Multimodal Fusion for Vietnamese Scene-Text Image Captioning: Dataset, Graph Framework, and Phonological Attention
Introduces ViTextCaps dataset and PhonoSTFG phonological graph fusion framework for Vietnamese scene-text image captioning, showing cross-modal graph edges harm performance.
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Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees
DSR is a neuro-symbolic autoformalization framework using operator trees that achieves new state-of-the-art results on the PRIME benchmark of 156 Lean 4 theorems.
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Event-based Civil Infrastructure Visual Defect Detection: ev-CIVIL Dataset and Benchmark
Presents the ev-CIVIL dataset and benchmark showing that event-based cameras can support real-time detection of cracks and spalling in civil infrastructure under challenging lighting.
-
Realistic Compound-Lens Defocus Blur Synthesis
A Debye CZT-based wave-optics pipeline generates lens-diverse synthetic defocus blur datasets that improve cross-device deblurring generalization over existing real and synthetic data.
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Training-free Controllable Human Motion Generation under Heterogeneous Constraints
MIC casts diffusion motion generation as stochastic control to support both objective-based and criterion-based constraints without training or differentiability requirements.
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Drag, Infer, Reproject: Grounding LLMs through Spatial Interaction for Image Clustering
CriterionSI infers clustering criteria from sequential user drags via LLMs to produce progressively aligned image cluster layouts.
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SENTRY: SAM2-Enhanced Neighbor-Aware and Temporally Reasoned Memory for Visual Tracking
SENTRY is a plug-and-play module that replaces confidence-based memory writes with neighbor-aware cycle-consistent validation in SAM2 trackers, yielding new zero-shot SOTA results on LaSOT, GOT-10k and other benchmarks.
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Differential Unfolding: Efficient Unfolding Reconstruction for Video Snapshot Compressive Imaging
Differential Unfolding replaces uniform stacking in deep unfolding networks with a heterogeneous structure of anchoring and differential evolution stages to achieve better accuracy-efficiency trade-offs in video SCI reconstruction.
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Seeing What Matters: Perceptual Wrapper with Common Randomness for 3D Gaussian Splatting
A plug-and-play perceptual wrapper using common random noise and Wasserstein Distortion supervision improves texture quality and reduces model size in 3D Gaussian Splatting.
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The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset
KITScenes Multimodal presents a new multimodal autonomous driving dataset with complete HD maps and four benchmarks for spatial learning tasks including online map construction and end-to-end driving.
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Silent Failures in Federated Personalization of Foundation Models
Federated personalization of foundation models creates hard-to-detect trustworthiness failures due to privacy constraints, and existing benchmarks cannot adequately evaluate them.
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RefDiffNet: Learning to Expose Subtle PCB Defects Before Detection
RefDiffNet is a lightweight input enhancement block that uses reference image comparison to expose PCB defects, delivering up to 18% relative mAP50:95 gains across YOLO, RT-DETR, and Faster R-CNN detectors with 0.004-0.005M extra parameters.
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Decomposed Vision-Language Alignment for Fine-Grained Open-Vocabulary Segmentation
Decomposed Vision-Language Alignment framework factorizes prompts into concept and attribute tokens with Feature-Gated Cross-Attention for better compositional generalization in fine-grained open-vocabulary segmentation.
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MetaSR: Content-Adaptive Metadata Orchestration for Generative Super-Resolution
MetaSR adaptively orchestrates metadata in a DiT-based generative SR model to deliver up to 1 dB PSNR gains and 50% bitrate savings across diverse content and degradations.
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Cognitive Pivot Points and Visual Anchoring: Unveiling and Rectifying Hallucinations in Multimodal Reasoning Models
Hallucinations in multimodal reasoners cluster at high-entropy pivot tokens due to intermediate-layer visual anchoring failure, and V-STAR mitigates this with attention rewards plus forced reflection.
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Fast Model-guided Instance-wise Adaptation Framework for Real-world Pansharpening with Fidelity Constraints
FMG-Pan is a model-guided instance-wise adaptation framework for real-world pansharpening that adds physical fidelity constraints to deliver state-of-the-art fusion quality with training and inference completed in seconds on single image pairs.
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Binno: A 1st-order method for Bi-level Nonconvex Nonsmooth Optimization for Matrix Factorizations
Binno is a proximal-gradient first-order algorithm for nonconvex nonsmooth bi-level optimization, shown on sparse low-rank matrix factorization and regularized market-clearing problems with reported gains over baselines.
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Measuring the stability and plasticity of recommender systems
A new offline protocol to profile recommender algorithms by stability in retaining past patterns and plasticity in adapting to changes upon retraining, with preliminary results on the GoodReads dataset.
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Why Do Class-Dependent Evaluation Effects Occur with Time Series Feature Attributions? A Synthetic Data Investigation
Synthetic experiments reveal that class-dependent effects appear in both perturbation-based and ground-truth evaluations of time series feature attributions, often producing contradictory rankings of attribution quality due to differences in feature amplitude or temporal extent between classes.
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NFR: Neural Feature-Guided Non-Rigid Shape Registration
NFR combines neural features with dynamic consistency-filtered geometric registration to achieve robust non-rigid 3D shape matching without annotated correspondences.
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TVTA: Trajectory-Aware Viseme-Guided Temporal Aggregation for Event-Based Lip Reading
Trajectory-aware local temporal modeling before spatial aggregation plus CTC viseme supervision and EMA consistency lifts DVS-Lip word accuracy to 77.49%.
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FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection
FSDC-DETR improves small-object AP by 6.8–6.9 points on VisDrone and AITODv2 by explicit frequency-spatial fusion and wavelet-style downsampling inside a DETR hybrid encoder.
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Toward a Scientific Discovery Engine for Weather and Climate Data: A Visual Analytics Workbench for Embedding-Based Exploration
An open-source visual analytics workbench enables provenance-aware, interactive embedding-based retrieval of weather and climate analogs, scalable to tens of millions of embeddings on commodity hardware.
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RACT: Retrieval Augmented Column-Table Learning and Prediction for Multi-Table Schema Matching
RACT is a retrieval-augmented self-supervised method that improves multi-table schema matching precision and completeness by up to 70% by probabilistically retrieving relevant tables to limit column candidate search space.
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Unified Driving Tokens: Representation- and Geometry-Guided Discrete Tokenizer for Driving World Models and Planning
A representation- and geometry-guided discrete tokenizer for driving scenes improves token quality for world models and planning on NAVSIM.
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ProtoPathway: Biologically Structured Prototype-Pathway Fusion for Multimodal Cancer Survival Prediction
ProtoPathway fuses prototype-based histopathology encoding with pathway-aware graph neural networks for multimodal cancer survival prediction and native biological attribution.
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Shortcut Mitigation via Spurious-Positive Samples
A method uses spurious-positive samples to identify and regularize neurons that rely on spurious features, improving model robustness without extra annotations or balanced data.
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Evaluating Generative Models as Interactive Emergent Representations of Human-Like Collaborative Behavior
Embodied LLM agents exhibit emergent collaborative behaviors indicating mental models of partners in a color-matching game, detected via LLM judges and supported by positive user feedback.
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Metric Unreliability in Multimodal Machine Unlearning: A Systematic Analysis and Principled Unified Score
Standard unlearning metrics disagree in multimodal settings, but a correlation-weighted Unified Quality Score delivers consistent method rankings across benchmarks.
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Cross Paradigm Representation and Alignment Transformer for Image Deraining
CPRAformer fuses spatial-channel and global-local attention paradigms via SPC-SA, SPR-SA, and AAFM to achieve state-of-the-art image deraining on eight benchmarks.
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Listen, Look, and Learn: Learning Without Forgetting through SAM-Audio
Integrates SAM-Audio dense representations with guided attention and dual distillation for audio-visual class-incremental learning, reporting consistent outperformance on benchmarks.
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Real-Time Frame- and Event-based Object Detection with Spiking Neural Networks on Edge Neuromorphic Hardware: Design, Deployment and Benchmark
SNNs deployed on Loihi 2 achieve real-time object detection with the lowest dynamic energy per inference and recover 87-100% of ANN accuracy via distillation-aware training.
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CoRE: Concept-Reasoning Expansion for Continual Brain Lesion Segmentation
CoRE aligns image tokens to a hierarchical concept library to simulate clinical reasoning for expert routing and demand-based growth in continual brain lesion segmentation, achieving SOTA on 12 tasks.
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Autonomous Unmanned Aircraft Systems for Enhanced Search and Rescue of Drowning Swimmers: Image-Based Localization and Mission Simulation
A UAS with YOLO-based swimmer detection and DES simulations reduces drowning rescue response time by a factor of five versus standard operations in tested lake areas.
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SCULPT: An Interactive Machine Learning Platform for Analyzing Multi-Particle Coincidence Data from Cold Target Recoil Ion Momentum Spectroscopy
SCULPT is an interactive machine learning platform combining UMAP, clustering, and adaptive confidence scoring for analyzing COLTRIMS multi-particle coincidence data.
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Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions
A survey of trajectory prediction techniques for autonomous vehicles that proposes a taxonomy, overviews the prediction pipeline, and highlights remaining research gaps.
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TwinLiteNet+: An Enhanced Multi-Task Segmentation Model for Autonomous Driving
TwinLiteNet+ is a hybrid-encoder multi-task segmentation model with new UCB, USB, and PCAA modules that reports 92.9% mIoU on drivable area and 34.2% IoU on lane segmentation on BDD100K while using 11x fewer FLOPs than prior models.
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Aesthetic Attributes Assessment of Images
The paper proposes the Aesthetic Multi-Attribute Network (AMAN) that jointly predicts captions and scores for five aesthetic attributes using a new weakly-labeled dataset created via knowledge transfer.
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Exploring Multi-Modal Large Language Models and Two-Stage Fine-Tuning for Fashion Image Retrieval
Framework uses LLaVA for triplet generation and two-stage fine-tuning to enhance composed fashion image retrieval.
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Generalization Under Scrutiny: Cross-Domain Detection Progresses, Pitfalls, and Persistent Challenges
A survey that organizes methods for cross-domain object detection into a taxonomy, analyzes domain shift across detection stages, and outlines persistent challenges.
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RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques
A survey of RGB-D object detection from traditional hand-crafted features with machine learning to deep learning techniques.
- PDE-Agents: An LLM-Orchestrated Multi-Agent Framework for Automated Finite Element Simulations with Knowledge Graph-Augmented Reasoning