Every paper checked — nothing hidden

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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
Event Cameras versus Frame Cameras for Synthetic-Aperture Imaging: A Simulation Study Compares event and conventional frame cameras via simulations for synthetic-aperture imaging through occluding scenes like foliage. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on airborne synthetic-aperture imaging simulations rather than industrial inspection or defect detection.
Event Cameras versus Frame Cameras for Synthetic-Aperture Imaging: A Simulation Study Compares event and conventional frame cameras via simulations for synthetic-aperture imaging through occluding scenes like foliage. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Deals with event camera optical integration rather than multimodal vision-language models.
InfiniSplat v2: Analyzing and Improving Feed-Forward 3DGS from Any Views Decouples geometry and appearance learning in Gaussian reconstruction to improve three-dimensional scene rendering across diverse views. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses on 3D novel view synthesis, not multimodal cross-modal modeling.
InfiniSplat v2: Analyzing and Improving Feed-Forward 3DGS from Any Views Decouples geometry and appearance learning in Gaussian reconstruction to improve three-dimensional scene rendering across diverse views. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Novel view 3D Gaussian reconstruction, not industrial visual inspection.
ReferFlow: Beyond Final-Target Localization for Complex Referring Expressions This paper introduces ReferFlow-Bench and an accompanying method to evaluate and perform multi-step trajectory-level referring expression comprehension. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Referring expression comprehension, not industrial defect detection.
Look Before You Restore: Learning to Predict Before Acting for Agentic Image Restoration This paper proposes PreActIR, an agentic image restoration framework that forecasts tool consequences using a world model before taking action. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Agentic natural image restoration, not industrial manufacturing inspection.
STP-GUI: Spatially-Aware Token Pruning for Efficient Web-GUI Agents This paper introduces STP-GUI, a spatially aware token-pruning framework that preserves local interface structures for efficient web-GUI vision-language agents. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Web GUI screenshot processing, not industrial visual inspection.
Where Should the Gaussians Go? Reusable Label-Aware Allocation for Budget-Constrained Gaussian Splatting of Cinematic CT This paper proposes a reusable, label-aware front end to allocate fixed budgets of 3D Gaussians for cinematic CT visualization without per-case optimization. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Medical CT scan 3D Gaussian splatting, not industrial inspection.
Where Should the Gaussians Go? Reusable Label-Aware Allocation for Budget-Constrained Gaussian Splatting of Cinematic CT This paper proposes a reusable, label-aware front end to allocate fixed budgets of 3D Gaussians for cinematic CT visualization without per-case optimization. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Deals with CT rendering techniques, not multimodal vision-language understanding.
Hybrid supervised instance segmentation by learning label noise suppression This paper presents a hybrid instance segmentation pipeline that trains ancillary models to suppress label noise when combining bounding boxes with pixel masks. Peer-reviewed	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Focuses strictly on unimodal computer vision instance segmentation.
Hybrid supervised instance segmentation by learning label noise suppression This paper presents a hybrid instance segmentation pipeline that trains ancillary models to suppress label noise when combining bounding boxes with pixel masks. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Instance segmentation on standard benchmark datasets, not industrial defects.
Infant Fingerprints: Quality Assessment & Recognition This paper assesses ten fingerprint quality assessment methods on longitudinal infant data and proposes parameter tuning routines to improve recognition. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Biometric infant fingerprinting, not industrial visual quality control.
Infant Fingerprints: Quality Assessment & Recognition This paper assesses ten fingerprint quality assessment methods on longitudinal infant data and proposes parameter tuning routines to improve recognition. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Biometric image processing, not multimodal reasoning across multiple modalities.
OLiVES: An Outdoor Low-Light Video Benchmark for Enhancement and Segmentation This paper introduces OLiVES, a benchmark dataset of dynamic outdoor low-light videos designed for joint video enhancement and object segmentation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Outdoor low-light video enhancement, not industrial production inspection.
Generative Representation Learning for Scalable Latent Tokenization This paper develops a self-supervised representation learning approach based on pointwise mutual information factorisation for scalable generative latent tokenization. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Evaluates image tokenizers, not LLM benchmarks or evaluation methods.
Generative Representation Learning for Scalable Latent Tokenization This paper develops a self-supervised representation learning approach based on pointwise mutual information factorisation for scalable generative latent tokenization. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Self-supervised generative tokenization, not industrial inspection.
Generative Representation Learning for Scalable Latent Tokenization This paper develops a self-supervised representation learning approach based on pointwise mutual information factorisation for scalable generative latent tokenization. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on representation learning efficiency, not deployment safety or guardrails.
Reliability-Aware Multimodal Sentiment Prediction Under Local Modality Missingness This paper introduces RM-Net, a reliability-aware network designed to maintain multimodal sentiment prediction accuracy when spans of modalities are missing. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Sentiment prediction from speech/video, not industrial manufacturing vision.
Speculative Sampling in Interactive Video Generation This paper proposes Speculative Sampling to combine large bidirectional sampling windows with low-latency interaction in interactive video generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Interactive video generation sampling, not industrial quality control.
A$^3$PreCore: Robust Rigid Registration for Native FLAIR-Space Brain-Mask Transfer This paper presents A3PreCore, a six-degree-of-freedom rigid-registration method for robust T1-to-FLAIR brain-mask transfer alongside quantitative quality control metrics. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Medical brain MRI registration, not factory production visual inspection.
A$^3$PreCore: Robust Rigid Registration for Native FLAIR-Space Brain-Mask Transfer This paper presents A3PreCore, a six-degree-of-freedom rigid-registration method for robust T1-to-FLAIR brain-mask transfer alongside quantitative quality control metrics. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Specific medical image registration technique, not multimodal language-vision models.
Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation This paper introduces Any Time, Any Space, a world-state memory framework enabling consistent multi-shot long-form agentic video generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Screenplay-to-video generation, not industrial manufacturing vision.
Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes This paper proposes a mixture-of-experts transformer architecture using discrete Hodge-Laplacian operators to solve steady partial differential equations on unstructured meshes. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Numerical PDE surrogate architecture, not multimodal reasoning models.
Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes This paper proposes a mixture-of-experts transformer architecture using discrete Hodge-Laplacian operators to solve steady partial differential equations on unstructured meshes. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Surrogate PDE solver for fluid dynamics, not computer vision.
Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes This paper proposes a mixture-of-experts transformer architecture using discrete Hodge-Laplacian operators to solve steady partial differential equations on unstructured meshes. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Focuses on mesh PDE solving, not language model efficiency.
Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes This paper proposes a mixture-of-experts transformer architecture using discrete Hodge-Laplacian operators to solve steady partial differential equations on unstructured meshes. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Deals with fluid dynamics simulation accuracy, not AI deployment safety.
Learnable Hodge-Laplacian Driven Mixture of Experts for Steady-PDE Surrogates on Coarse Unstructured Meshes This paper proposes a mixture-of-experts transformer architecture using discrete Hodge-Laplacian operators to solve steady partial differential equations on unstructured meshes. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Evaluates fluid dynamics surrogate models, not language model benchmarks.
Feed-Forward Multi-View Feature Coding for 3D Gaussian Splatting This paper presents a feed-forward framework that encodes multi-view image features into a compact bitstream for 3D Gaussian Splatting scene reconstruction. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant 3D scene reconstruction and compression, not multimodal text-image-audio integration.
Feed-Forward Multi-View Feature Coding for 3D Gaussian Splatting This paper presents a feed-forward framework that encodes multi-view image features into a compact bitstream for 3D Gaussian Splatting scene reconstruction. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Novel view 3D Gaussian splatting, not industrial defect detection.
GeoThinker-$F$: Endogenous Predictive World Representations for Fast Spatial Intelligence This paper proposes GeoThinker-F, an efficient architecture that predicts spatial representations directly from multimodal hidden states without dedicated 3D encoders. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant General 3D MLLM representation, not manufacturing anomaly detection.
DynThinker: Unifying Static 3D and Dynamic 4D Spatial Reasoning This paper presents DynThinker, a framework using parameter averaging and spatial-dynamic fusion to balance static 3D and dynamic 4D reasoning. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant General 3D/4D spatial reasoning, not industrial quality control.
CommerceGen-Studio: An End-to-End Framework for Commercial-Grade Main-Image Generation This paper introduces CommerceGen-Studio, an end-to-end framework using specialized agents and diffusion models to generate e-commerce product images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant E-commerce marketing image generation, not industrial manufacturing inspection.
VITAL: From Visual Motion to Precise Action This paper presents VITAL, an action tokenizer coupling visual motion scaffolding with residual error encoding for autonomous driving decision-making. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Autonomous driving trajectory prediction, not industrial visual inspection.
Representation Conditioning for Generation This paper proposes representation conditioning to feed vision encoder features into later layers of diffusion transformers for improved generation semantics. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on diffusion training, not industrial inspection or defect detection.
Can Learning to Answer Spatial Questions Improve Novel-View Generation? This paper introduces Ask4NV, combining multimodal 3D language understanding with camera geometry to guide novel-view image generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on novel-view image generation, not industrial inspection or defect detection.
An Initial Study of Physiological Markers for Deepfake Speech Detection This paper investigates 36 handcrafted physiological markers from speech production to detect deepfake speech using standard classifiers. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Targets audio deepfake detection rather than AI deployment guardrails, safety, or robustness.
An Initial Study of Physiological Markers for Deepfake Speech Detection This paper investigates 36 handcrafted physiological markers from speech production to detect deepfake speech using standard classifiers. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Explores speech feature engineering, not model compression or efficient inference.
An Initial Study of Physiological Markers for Deepfake Speech Detection This paper investigates 36 handcrafted physiological markers from speech production to detect deepfake speech using standard classifiers. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Studies physiological speech markers, not LLM evaluation or benchmark methodology.
An Initial Study of Physiological Markers for Deepfake Speech Detection This paper investigates 36 handcrafted physiological markers from speech production to detect deepfake speech using standard classifiers. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on speech audio deepfake detection, not industrial vision inspection.
An Initial Study of Physiological Markers for Deepfake Speech Detection This paper investigates 36 handcrafted physiological markers from speech production to detect deepfake speech using standard classifiers. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Studies audio speech production markers exclusively, not multimodal vision-language models.
Physical Layer Anomaly Detection via Adaptive Gaussian Mixture Model This paper proposes an adaptive Gaussian mixture model framework to detect physical-layer channel state information spoofing attacks in wireless localization. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on wireless signal physical-layer spoofing, not AI deployment safety.
Physical Layer Anomaly Detection via Adaptive Gaussian Mixture Model This paper proposes an adaptive Gaussian mixture model framework to detect physical-layer channel state information spoofing attacks in wireless localization. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Applies standard GMMs to wireless signals, not efficient neural model serving.
Physical Layer Anomaly Detection via Adaptive Gaussian Mixture Model This paper proposes an adaptive Gaussian mixture model framework to detect physical-layer channel state information spoofing attacks in wireless localization. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Analyzes physical wireless CSI anomaly detection, not LLM evaluation benchmarks.
Limits of Statistical Assurance for Embodied and Agentic AI under Adaptive Adversaries This paper analyzes the mathematical limits of statistical safety certification for embodied and agentic AI facing adaptive adversaries. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Theoretical analysis of safety bounds under adaptive adversaries, not benchmark evaluation methodology.
Limits of Statistical Assurance for Embodied and Agentic AI under Adaptive Adversaries This paper analyzes the mathematical limits of statistical safety certification for embodied and agentic AI facing adaptive adversaries. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Addresses theoretical adversary testing bounds, not efficient serving or model compression.
Combining Post-Quantum Cryptography and Quantum Key Distribution: Taxonomy, Constructions, Proofs, Standards, Deployments and Open Problems This survey provides an eight-dimension taxonomy and comparative analysis of hybrid protocols combining post-quantum cryptography with quantum key distribution. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Discusses post-quantum cryptography key distribution protocols, not AI safety or deployment.
TrackShield: An Efficient Runtime Defense Against Availability Attacks on High-Performance Real-Time Multi-Object Tracking This paper presents TrackShield, a runtime resource-management layer that protects multi-object tracking pipelines from availability attacks by enforcing deterministic admission control. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Protects classical multi-object tracking pipelines from availability attacks, not AI safety.
Did the LLM Answer the Question? A Semantic Reconstruction Game for Jailbreak Evaluation This paper proposes a semantic reconstruction game to accurately evaluate jailbreak success by filtering out harmless repetitions and refusals. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Focuses on jailbreak evaluation accuracy, not model compression or efficient serving.
AutoPoly-HE: Autonomous Design of Polynomial Activations for Privacy-Preserving Encrypted Inference The authors propose AutoPoly-HE, a framework that automatically selects dataset-tailored polynomial activations for homomorphic encrypted neural network inference. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on homomorphic encryption activations rather than AI deployment safety and robustness.
Differentially Private Learning of Markov Chains: Near-Optimal Sample Complexity for Item and User Level Privacy This paper establishes sample complexity bounds for differentially private estimation of Markov chain transition matrices under item and user privacy. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Addresses theoretical differential privacy for Markov chains, not deployment AI safety.
Quantum-Resilient Secure Protocol for Decentralized Edge-IoT Peer-to-Peer Energy Trading Systems The authors present a post-quantum authenticated key agreement protocol for decentralized edge peer-to-peer energy trading systems. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Deals with quantum key distribution for IoT energy trading, not AI safety.
What You Sign Is Not What You Run: The Verifiability Gap in Quantized LLM Supply Chains This paper examines the verifiability gap in quantized model supply chains, showing that common GGUF artifacts lack necessary build environment disclosures. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Focuses on artifact reproducibility in supply chains, not LLM benchmark evaluation.
Mission (Im)Possible: Towards Autonomous Discovery of Autopilot Logic Flaws in Open-Source Drone Frameworks The authors present an approach using domain-informed language models to discover semantic logic flaws in open-source drone autopilot software. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on testing drone software rather than AI model safety, guardrails, or robustness.
A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference This paper constructs an empirical graph of 62 private transformer inference systems to evaluate comparability, cryptographic progress, and scaling behavior. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Focuses on cryptographic secure computation, not model compression, distillation, or quantization.
A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference This paper constructs an empirical graph of 62 private transformer inference systems to evaluate comparability, cryptographic progress, and scaling behavior. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Analyzes cryptographic inference protocols, not LLM capabilities or evaluation benchmarks.
No Way To Steal My Face: Proactive Defense Against Identity-Preserving Personalized Generation The authors present IDGuardian, an adversarial perturbation framework designed to defend facial images against unauthorized personalized diffusion models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 15:06	Not relevant Focuses on personal facial privacy in diffusion models, not industrial manufacturing vision.
No Way To Steal My Face: Proactive Defense Against Identity-Preserving Personalized Generation The authors present IDGuardian, an adversarial perturbation framework designed to defend facial images against unauthorized personalized diffusion models. Preprint	Multimodal models via arxiv · 15 Oct, 15:06	Not relevant Addresses image diffusion personalization defense, not multimodal reasoning or vision-language models.
Analyzing and Mitigating Poisoning Attacks on Flow-Based Intrusion Detection This paper analyzes latent backdoor poisoning in flow-based intrusion detection and introduces a perturbation-based diagnostic and mitigation methodology. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 15:06	Not relevant Focuses on network intrusion detection systems rather than AI deployment safety and robustness.
Analyzing and Mitigating Poisoning Attacks on Flow-Based Intrusion Detection This paper analyzes latent backdoor poisoning in flow-based intrusion detection and introduces a perturbation-based diagnostic and mitigation methodology. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 15:06	Not relevant Studies network backdoor attacks, not LLM evaluation benchmarks or methodologies.
Analyzing and Mitigating Poisoning Attacks on Flow-Based Intrusion Detection This paper analyzes latent backdoor poisoning in flow-based intrusion detection and introduces a perturbation-based diagnostic and mitigation methodology. Preprint	Small and efficient models via arxiv · 15 Oct, 15:06	Not relevant Uses pruning solely for backdoor defense in intrusion detection, not efficient inference.

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