Every paper checked — nothing hidden

All papers

Every paper checked for brief #4 of 12–19 Oct 2026 — nothing is hidden. Brief papers first.

All17,313 In brief24 More (on-topic)3,333 Not relevant13,754 Not assessed87 Older352 Could not confirm93 Blogs with no paper266 All blogs284

Paper	Topic	Relevance
Human Pose Estimation by Probabilistic Mixtures of Gaussian and Uniform Distributions The paper proposes a continuous probabilistic Gaussian mixture framework to improve human pose estimation under dense occlusions without retraining models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Covers pose estimation robustness rather than LLM deployment safety, jailbreaks, or hallucinations.
Human Pose Estimation by Probabilistic Mixtures of Gaussian and Uniform Distributions The paper proposes a continuous probabilistic Gaussian mixture framework to improve human pose estimation under dense occlusions without retraining models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on general human pose estimation rather than industrial inspection or defect detection.
Human Pose Estimation by Probabilistic Mixtures of Gaussian and Uniform Distributions The paper proposes a continuous probabilistic Gaussian mixture framework to improve human pose estimation under dense occlusions without retraining models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Introduces a pose estimation framework, not an LLM benchmark or evaluation methodology.
Human Pose Estimation by Probabilistic Mixtures of Gaussian and Uniform Distributions The paper proposes a continuous probabilistic Gaussian mixture framework to improve human pose estimation under dense occlusions without retraining models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with computer vision pose heatmaps, not multimodal text-image foundation models.
Scenes as an Attack Surface: Uncovering Scene-Grounded Safety Failures in MLLMs The paper introduces a benchmark to show that visual scene semantics alone can cause multimodal models to bypass safety guardrails without adversarial prompts. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies multimodal LLM jailbreaks, not industrial inspection or defect detection.
RePrior: Measurement-Reconciled Prior Correction for Sparse-View CBCT Reconstruction The paper introduces a multi-stage framework that corrects learned priors using X-ray measurements for sparse-view computed tomography reconstruction. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses 3D CT volumetric reconstruction, not multimodal vision-language models or cross-modal reasoning.
RePrior: Measurement-Reconciled Prior Correction for Sparse-View CBCT Reconstruction The paper introduces a multi-stage framework that corrects learned priors using X-ray measurements for sparse-view computed tomography reconstruction. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical CT reconstruction rather than industrial inspection or defect detection.
Temporal Diffusion Bridge Model for Vessel Extraction Using Physics-informed Synthetic Data The paper presents a temporal diffusion bridge model trained on physics-based synthetic data to extract coronary arteries from angiograms without manual labels. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical X-ray image translation, not multimodal models.
Temporal Diffusion Bridge Model for Vessel Extraction Using Physics-informed Synthetic Data The paper presents a temporal diffusion bridge model trained on physics-based synthetic data to extract coronary arteries from angiograms without manual labels. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on coronary angiography vessel extraction, not industrial inspection.
Neural Block-wise Auto-exposure for Single-Shot High Dynamic Range Imaging The paper proposes a neural block-wise auto-exposure method for single-shot high dynamic range imaging to reduce visual artifacts. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on camera hardware auto-exposure algorithms, not multimodal models.
Neural Block-wise Auto-exposure for Single-Shot High Dynamic Range Imaging The paper proposes a neural block-wise auto-exposure method for single-shot high dynamic range imaging to reduce visual artifacts. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on camera exposure for HDR imaging, not industrial inspection.
Exploring the Latent Structure of AMD Severity Using Retinal Foundation Models The paper examines how retinal foundation model embeddings represent macular degeneration severity and how that latent structure affects downstream prediction. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Analyzes retinal foundation model embeddings, not general multimodal models.
Exploring the Latent Structure of AMD Severity Using Retinal Foundation Models The paper examines how retinal foundation model embeddings represent macular degeneration severity and how that latent structure affects downstream prediction. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Investigates retinal disease diagnosis, not industrial defect detection.
Frozen Site-Probe Accuracy Is Not a Standalone Harmonization Score: An Audit of Evaluation Practice for Multi-Site MRI The paper audits frozen site-probe evaluation for multi-site brain MRI harmonization and finds probe accuracy is an unreliable standalone metric. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical brain MRI site harmonization, not multimodal models.
Frozen Site-Probe Accuracy Is Not a Standalone Harmonization Score: An Audit of Evaluation Practice for Multi-Site MRI The paper audits frozen site-probe evaluation for multi-site brain MRI harmonization and finds probe accuracy is an unreliable standalone metric. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on multi-site MRI harmonization evaluation, not industrial inspection.
C$^2$LUE: Clinically Aligned Patient-Level Ultrasound Diagnosis via Evidence-Aware Multi-Instance Learning This paper proposes a multi-instance learning model with risk-aligned regularization for patient-level ultrasound diagnostic classification. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with medical ultrasound diagnosis, not industrial inspection.
C$^2$LUE: Clinically Aligned Patient-Level Ultrasound Diagnosis via Evidence-Aware Multi-Instance Learning This paper proposes a multi-instance learning model with risk-aligned regularization for patient-level ultrasound diagnostic classification. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical multi-instance learning for ultrasound, not multimodal models.
TrajCFG: Token-Wise Classifier-Free Guidance via Denoising Trajectory Feedback This paper introduces a training-free method adjusting token-wise guidance scales based on velocity trajectory directional changes in generative models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies classifier-free guidance in generative diffusion, not industrial inspection.
TrajCFG: Token-Wise Classifier-Free Guidance via Denoising Trajectory Feedback This paper introduces a training-free method adjusting token-wise guidance scales based on velocity trajectory directional changes in generative models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on sampling algorithms for generative diffusion across modalities.
Axiom-0: Hierarchical Self-Refinement for Vision-Language-Action Policies This paper introduces a vision-language-action policy using hierarchical self-refinement across internal representations and action interfaces. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on general robotic manipulation, not industrial defect detection.
Video-Arena: A Scalable Agentic Video Benchmark for Spatiotemporal Capability This paper introduces a video benchmark derived from competitive game records to evaluate dynamic spatiotemporal world state tracking. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates game video understanding, not industrial visual inspection.
Disentangling Task-Relevant Latent Dynamics for Reward Modeling This paper proposes a latent dynamics model to learn dense robotic manipulation rewards from videos without confounding visual distractors. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on reinforcement learning reward modeling from video, not multimodal models.
Disentangling Task-Relevant Latent Dynamics for Reward Modeling This paper proposes a latent dynamics model to learn dense robotic manipulation rewards from videos without confounding visual distractors. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on robotic manipulation rewards, not manufacturing inspection.
Semantic Edge-Cloud Communication for Real-Time Urban Traffic Digital Twins This paper presents a semantic edge-to-cloud communication method to reduce transmission bandwidth for real-time urban traffic digital twins. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses urban traffic digital twins, not industrial visual inspection.
Semantic Edge-Cloud Communication for Real-Time Urban Traffic Digital Twins This paper presents a semantic edge-to-cloud communication method to reduce transmission bandwidth for real-time urban traffic digital twins. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on edge-cloud network communications, not multimodal model architectures.
ClothCode: Generative Modeling for Garment State Estimation and Dynamics Prediction This paper presents a discrete generative transformer framework for garment state estimation and dynamics prediction in robotic manipulation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on garment state estimation and dynamics, not multimodal models.
ClothCode: Generative Modeling for Garment State Estimation and Dynamics Prediction This paper presents a discrete generative transformer framework for garment state estimation and dynamics prediction in robotic manipulation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on robotic garment manipulation, not industrial inspection.
Token-Budgeted Candidate Retrieval for 3D Scene-Grounded VLMs: Category Names vs. Pairwise Geometry This paper evaluates category name matching versus pairwise geometry metrics for candidate retrieval in context-constrained 3D vision-language models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D scene grounding, not manufacturing or industrial inspection.
Token-Budgeted Candidate Retrieval for 3D Scene-Grounded VLMs: Category Names vs. Pairwise Geometry This paper evaluates category name matching versus pairwise geometry metrics for candidate retrieval in context-constrained 3D vision-language models. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Studies 3D grounding candidate retrieval rather than general LLM evaluation.
Token-Budgeted Candidate Retrieval for 3D Scene-Grounded VLMs: Category Names vs. Pairwise Geometry This paper evaluates category name matching versus pairwise geometry metrics for candidate retrieval in context-constrained 3D vision-language models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Studies context retrieval for 3D VLMs, not model compression.
Token-Budgeted Candidate Retrieval for 3D Scene-Grounded VLMs: Category Names vs. Pairwise Geometry This paper evaluates category name matching versus pairwise geometry metrics for candidate retrieval in context-constrained 3D vision-language models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on candidate retrieval efficiency, not safety or guardrails.
Agreement versus Softmax under Spatial Disambiguation This paper evaluates calibration differences between object-level softmax and agreement metrics when resolving ambiguous 3D referring queries. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies metric calibration in 3D referring, not AI safety or jailbreaks.
Agreement versus Softmax under Spatial Disambiguation This paper evaluates calibration differences between object-level softmax and agreement metrics when resolving ambiguous 3D referring queries. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Examines metric calibration in 3D referring, not model efficiency.
Agreement versus Softmax under Spatial Disambiguation This paper evaluates calibration differences between object-level softmax and agreement metrics when resolving ambiguous 3D referring queries. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses 3D visual grounding calibration, not industrial defect detection.
Agreement versus Softmax under Spatial Disambiguation This paper evaluates calibration differences between object-level softmax and agreement metrics when resolving ambiguous 3D referring queries. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D referring metric calibration rather than LLM evaluation.
SliderEdit++: Improved Slider Trajectories in Instruction-Based Image Editing This paper introduces a benchmark and a trajectory regularization method for continuous, fine-grained control in instruction-based image editing. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies instruction-based image editing sliders, not industrial defect detection.
SliderEdit++: Improved Slider Trajectories in Instruction-Based Image Editing This paper introduces a benchmark and a trajectory regularization method for continuous, fine-grained control in instruction-based image editing. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on image editing trajectory regularization, not multimodal reasoning.
Image Diffusion Models Are Good 3D Human Motion Generators This paper adapts image diffusion transformers to generate 3D human motion from text using joint-time representations. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D skeletal motion diffusion from text, not multimodal reasoning.
Image Diffusion Models Are Good 3D Human Motion Generators This paper adapts image diffusion transformers to generate 3D human motion from text using joint-time representations. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D human motion generation, not industrial inspection.
BigCell: Generating Gigapixel Whole-Slide Images This paper presents a flow-matching transformer pipeline to generate full gigapixel histopathology whole-slide images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with gigapixel histopathology imaging, not manufacturing inspection.
BigCell: Generating Gigapixel Whole-Slide Images This paper presents a flow-matching transformer pipeline to generate full gigapixel histopathology whole-slide images. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Focuses on generative image modeling rather than LLM evaluation benchmarks.
BigCell: Generating Gigapixel Whole-Slide Images This paper presents a flow-matching transformer pipeline to generate full gigapixel histopathology whole-slide images. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical image generation rather than deployment safety or jailbreaks.
BigCell: Generating Gigapixel Whole-Slide Images This paper presents a flow-matching transformer pipeline to generate full gigapixel histopathology whole-slide images. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Addresses large-scale histopathology generation, not small or efficient model compression.
BigCell: Generating Gigapixel Whole-Slide Images This paper presents a flow-matching transformer pipeline to generate full gigapixel histopathology whole-slide images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on generative vision transformers for pathology, not multimodal interaction.
Thinking with Images without Coordinates This paper introduces a method for multimodal models to reason over images using token-level latent regions instead of bounding-box coordinates. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies visual reasoning in VLMs, not industrial inspection.
TGSR: Text-Grounded Diffusion for Faithful Image Super-Resolution This paper presents a test-time diffusion method that suppresses text hallucinations during image super-resolution by selectively generating text. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on super-resolution text hallucination, not industrial defect detection.
TGSR: Text-Grounded Diffusion for Faithful Image Super-Resolution This paper presents a test-time diffusion method that suppresses text hallucinations during image super-resolution by selectively generating text. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses diffusion image super-resolution, not multimodal reasoning or vision-language models.
Manifold Navigation Learning Using Recurrent Networks: Efficient Training Techniques This paper develops an immersion-based recurrent network approach for trajectory tracking and navigation on curved geometric manifolds. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on theoretical manifold navigation, not industrial visual inspection.
Manifold Navigation Learning Using Recurrent Networks: Efficient Training Techniques This paper develops an immersion-based recurrent network approach for trajectory tracking and navigation on curved geometric manifolds. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on recurrent models on geometric manifolds, not multimodal vision-language.
Real-Time Traffic Density Estimation: A Hybrid Computer Vision and Predictive Machine Learning Pipeline This paper benchmarks a pipeline combining real-time object detection with recurrent neural networks to forecast short-term traffic density. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on traffic density estimation, not manufacturing or industrial inspection.
Real-Time Traffic Density Estimation: A Hybrid Computer Vision and Predictive Machine Learning Pipeline This paper benchmarks a pipeline combining real-time object detection with recurrent neural networks to forecast short-term traffic density. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Deals with vehicle detection and time-series estimation without multimodal models.
Learning Transferable World-Action Models from Task-Paired Human Videos This paper proposes pretraining world-action models by predicting future actions and frames across paired human demonstration videos. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Robot world-action modeling from human video, not industrial inspection or defect detection.
Learning Transferable World-Action Models from Task-Paired Human Videos This paper proposes pretraining world-action models by predicting future actions and frames across paired human demonstration videos. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on visual world-action models for robotics, not multimodal vision-language models.
VisualCoding: Learning Executable Skills for Reliable Visual Reasoning This paper introduces a framework that acquires and directly executes reusable visual programs to improve multimodal reasoning agent reliability. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Visual program acquisition for reasoning benchmarks, not industrial visual inspection.
Design Choices for Multimodal Transformer Learning with Missing and Longitudinal Healthcare Data This paper studies transformer architectural choices for handling missing modalities and longitudinal observations in multimodal healthcare datasets. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Healthcare multimodal clinical data, not industrial visual inspection or defect detection.
Design Choices for Multimodal Transformer Learning with Missing and Longitudinal Healthcare Data This paper studies transformer architectural choices for handling missing modalities and longitudinal observations in multimodal healthcare datasets. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies multimodal data fusion, not AI safety, guardrails, or jailbreaks.
Design Choices for Multimodal Transformer Learning with Missing and Longitudinal Healthcare Data This paper studies transformer architectural choices for handling missing modalities and longitudinal observations in multimodal healthcare datasets. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Investigates tokenization for missing data, not small or efficient model serving.
Design Choices for Multimodal Transformer Learning with Missing and Longitudinal Healthcare Data This paper studies transformer architectural choices for handling missing modalities and longitudinal observations in multimodal healthcare datasets. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Analyzes tabular healthcare data architectures, not LLM benchmarks or evaluation.
FreeCHROMA: Generative Chroma Keying from Unaligned Background References This paper introduces a parameter-efficient diffusion method to composite video foregrounds into unaligned background reference scenes. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on video background compositing and generation, not multimodal models.
FreeCHROMA: Generative Chroma Keying from Unaligned Background References This paper introduces a parameter-efficient diffusion method to composite video foregrounds into unaligned background reference scenes. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Video chroma keying for film production, not industrial defect detection.

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