Search: “inference”

PhysioAI: Clinical Knowledge-Guided Semantic Supervision for Skeleton-Based Physiotherapy Action Recognition

arXiv:2609.12491v1 Announce Type: new Abstract: Skeleton-based action recognition can support automated tracking of physiotherapy exercises, particularly in remote rehabilitation settings where contin

researcharxiv-cs-cv

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Research

PLSP (Pre-hoc Liminal Space Profiling): OOD Prediction over Detection -- An Anticipatory Approach for Machine Learning Model Reliability

DGX agent

arXiv:2609.12225v1 Announce Type: cross Abstract: Out-of-Distribution (OOD) data poses a significant threat to machine learning models, often leading to model failure during deployment. All existing O

researcharxiv-cs-cv

14 Sept 2026

R^2M: Real-Aware Residual Model Merging for Robust and Generalizable Deepfake Detection

arXiv:2509.24367v2 Announce Type: replace Abstract: Deepfake generators evolve rapidly, making exhaustive data collection and repeated retraining impractical. Unlike generic multi-task settings, deepf

Tutorials

Recurrent Dynamic Range Extension

arXiv:2609.13135v1 Announce Type: cross Abstract: We present an approach to progressively extend the highlights of an image. Instead of reconstructing the full dynamic range of a complex scene directl

tutorialsarxiv-cs-cv

Robust Policy Optimization via Adversarial Importance Sampling

arXiv:2609.13044v1 Announce Type: new Abstract: Significant progress has been made in safeguarding deep reinforcement learning (DRL) policies against input perturbations. Developing robust DRL involve

safetyarxiv-cs-lg

Scalable Discrete-to-Continuous Channel Simulation for Compression and Privacy

arXiv:2609.12067v1 Announce Type: new Abstract: Channel simulation has recently emerged as a useful component in machine learning systems where samples from a prescribed probability distribution are t

Scaling Online Complex Event Detection with Synthetic Supervision and Mamba-Based Neural Algorithmic Reasoning

model-releasesarxiv-cs-lg

arXiv:2502.07250v3 Announce Type: replace Abstract: Modern machine learning models excel at detecting individual actions, sounds, or scene attributes from short, localized observations. However, many

SCOPE-OPSD: Fisher-Conditioned Privileged Subspaces for On-Policy Self-Distillation

arXiv:2609.12579v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) scores student-generated prefixes with a solution-conditioned self-teacher, yet transfers supervision only through ne

safetyarxiv-cs-lg

Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models

arXiv:2609.13005v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance on a wide range of natural language tasks, and recent benchmarks suggest that they are inc

Applications

The Vienna 4G/5G Drive-Test Dataset

arXiv:2603.02638v2 Announce Type: replace-cross Abstract: Machine learning for mobile network analysis, planning, and optimization is often limited by the lack of large, comprehensive real-world datas

applicationsarxiv-cs-lg

Agents

TileNet: Tile-Based CNN-SVM Architecture for Autonomous Unmanned Aerial Systems Inspection of Flat Roofs

arXiv:2609.13013v1 Announce Type: new Abstract: Flat roofs are among the most influential components of the building envelope, governing both structural performance and thermal efficiency, and thereby

agentsarxiv-cs-cv

VertiFuseX: Generalizable Financial Forecasting via Multi-Stream Temporal Fusion

arXiv:2609.12793v1 Announce Type: new Abstract: Stock price prediction remains challenging due to the non-stationary and noisy nature of financial time series. Existing deep learning models often rely

When Connected Does Not Mean Similar: Charting the Homophily Boundary of SNAP-KG for Streaming Entity Integration

arXiv:2609.12356v1 Announce Type: new Abstract: SNAP-KG is a framework for assigning newly arriving entities to semantic communities in a growing knowledge graph (KG) using only their raw features, wi

Local Ai

Demystifying the Privacy-Utility Trade-off in LLM Interactions

arXiv:2609.10992v1 Announce Type: new Abstract: The integration of Large Language Models into daily tasks relies on context-rich instructions, inevitably exposing sensitive user information. Current p

local-aiarxiv-cs-ai

Four Generations of Quantum Biomedical Sensors

arXiv:2603.29944v3 Announce Type: replace-cross Abstract: Quantum sensing technologies offer transformative potential for ultra-sensitive biomedical sensing, yet their clinical translation remains con

researcharxiv-cs-ai

GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay

model-releasesarxiv-cs-ai

arXiv:2609.11923v1 Announce Type: cross Abstract: Counterfactual regret minimization (CFR) is one of the few large numerical workloads that still runs faster on CPUs than on GPUs. Each iteration sweep

Less can be More: What Aspects of Speech Drive End-of-Turn Detection

arXiv:2609.11066v1 Announce Type: cross Abstract: In conversational AI, detecting when a speaker has finished talking is crucial for natural turn taking. While recent work incorporates semantics, the

researcharxiv-cs-ai

Agents

Memory Compression for High-Fanout Agent Sandboxes

arXiv:2609.11294v1 Announce Type: new Abstract: High-fanout agent workloads create a growing memory bottleneck because a single task may spawn many concurrent sandbox sessions. Yet these sandboxes are

agentsarxiv-cs-ai

Role differentiation as ignition of a collective information engine: Structuration in Agent Populations

arXiv:2609.05442v2 Announce Type: cross Abstract: Informational active matter shows how measurement-informed decisions produce collective order, so far in systems that reach consensus. We design colle

safetyarxiv-cs-ai

X-RACE: XAI-assisted Recurrent neural network Attribution for Channel Estimation

arXiv:2609.11211v1 Announce Type: cross Abstract: Deep learning models, notably Long Short-Term Memory (LSTM), have demonstrated promising performance in channel estimation for high-mobility vehicular

researcharxiv-cs-ai

A Fragility Spectrum for Recursive Language-Model Training

arXiv:2609.11149v1 Announce Type: new Abstract: Model-generated text is finding its way back into training corpora, and there is plenty of evidence that training on such data over and over collapses o

A Training-Free, Alignment-Free Approach to Corporate Intelligence: Application to SEC Filings

arXiv:2609.11620v1 Announce Type: new Abstract: High-dimensional dense text embeddings and large language models face real obstacles in financial-disclosure analysis: context-window limits, hallucinat

AcFlow: Controlling Text-to-Image Diffusion Transformers via Learned Conditional Activation Flow

arXiv:2609.10723v1 Announce Type: new Abstract: Text-to-image diffusion transformers (DiTs) are powerful generators, yet direct prompting provides limited control interface for style intensity and can

AUC Maximization from Biased Positive-unlabeled Data with Confidence

arXiv:2609.10928v1 Announce Type: new Abstract: Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced binary classification. Although positiv

safetyarxiv-cs-lg

Applications

Bayesian quantum sensing using graybox machine learning

arXiv:2601.17465v2 Announce Type: replace-cross Abstract: Quantum sensors offer significant advantages over classical devices in spatial resolution and sensitivity, enabling transformative application

applicationsarxiv-cs-lg

Beyond Prompting: Efficient and Robust Contextual Biasing for Speech LLMs via Logit-Space Integration (LOGIC)

arXiv:2601.15397v3 Announce Type: replace-cross Abstract: The rapid emergence of new entities -- driven by cultural shifts, evolving trends, and personalized user data -- poses a significant challenge

BiHDTrans: binary hyperdimensional transformer for efficient multivariate time series classification

arXiv:2509.24425v2 Announce Type: replace Abstract: The proliferation of Internet-of-Things (IoT) devices has led to an unprecedented volume of multivariate time series (MTS) data, requiring efficient

Can LLMs Normalize Databases? A Benchmark and Multi-Agent Framework for Schema Normalization

arXiv:2609.11141v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate structured outputs, but their reliability remains unclear when those outputs must satisfy

Agents

Cognitive Digital Twins: Ethical Risks and Governance for AI Systems That Model the Mind

arXiv:2606.23094v2 Announce Type: replace-cross Abstract: As AI systems become increasingly persistent and personalized, they make possible a class of technologies that we call cognitive digital twins

agentsarxiv-cs-cl

Hardware

Composable CXL Memory as a Kubernetes-Native Shared Memory for LLM Serving

arXiv:2609.10790v1 Announce Type: cross Abstract: We present a Kubernetes Dynamic Resource Allocation (DRA) driver that makes composable CXL memory a schedulable cluster resource, and evaluate the res

hardwarearxiv-cs-lg

Local Ai

Cross-Lingual Clinical Annotation Projection as Constrained Text Generation: A Six-Language Study

arXiv:2609.11450v1 Announce Type: new Abstract: Background: To determine whether cross-lingual clinical annotation projection can be formulated as a text-preserving, document-level generative task tha

local-aiarxiv-cs-cl

Applications

Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

arXiv:2609.11777v1 Announce Type: cross Abstract: Clinical electroencephalography (EEG) data are valuable for healthcare research and for developing artificial intelligence (AI)-based clinical decisio

applicationsarxiv-cs-lg

DirectSwap: Paired, Mask-Free Video Head Swapping with Full-Reference Evaluation

arXiv:2512.09417v2 Announce Type: replace Abstract: Head swapping replaces an entire head while preserving pose, expression, body motion, and scene. Progress is limited by the lack of cross-identity p

Distance generalization in transformers: why bother with positional encoding?

arXiv:2609.11913v1 Announce Type: new Abstract: Out-of-distribution length generalization, namely to extrapolate a task from short to longer context, has been studied intensively for transformers. Her

researcharxiv-cs-cl

Domain-Specific Hallucination Detection in Large Language Models

arXiv:2609.11878v1 Announce Type: new Abstract: Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detectio

DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction

arXiv:2609.10796v1 Announce Type: new Abstract: Pretrained diabetic retinopathy (DR) prediction models differ in their input fields, serialization formats, preprocessing requirements, and output seman

FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling

arXiv:2506.07350v2 Announce Type: replace-cross Abstract: Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot

FlexComp: One Model for Every Ratio in Context Compression

arXiv:2609.11192v1 Announce Type: new Abstract: Soft context compression condenses a context into a few memory tokens that a frozen LLM consumes in place of the raw text, but existing compressors fix

researcharxiv-cs-cl

Local Ai

FreeFlow: A Bias-free Hierarchical Transformer for Optical Flow Estimation

arXiv:2609.11486v1 Announce Type: new Abstract: Optical flow methods typically rely on task-specific inductive biases, such as correlation volumes, feature warping, and iterative refinement, among oth

local-aiarxiv-cs-cv

From Repetition to Recognition: Inductive Discovery of Disinformation Narratives

arXiv:2609.11128v1 Announce Type: new Abstract: In disinformation datasets, narratives are often understood as recurring interpretive patterns that group texts under narrative labels. Recent work form

researcharxiv-cs-cl

Halo: Improving forecast accuracy through heteroscedastic estimation

model-releasesarxiv-cs-lg

arXiv:2609.10589v1 Announce Type: new Abstract: Heteroscedastic forecasting, where a network estimates a scale parameter alongside a location parameter, is normally motivated by uncertainty quantifica

HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention

model-releasesarxiv-cs-lg

arXiv:2603.28458v4 Announce Type: replace Abstract: Token-level sparse attention mechanisms, exemplified by DeepSeek Sparse Attention (DSA), achieve fine-grained key selection by scoring every histori

HuRo: Robotizing Human Videos for Scalable VLA Pretraining

arXiv:2609.10706v1 Announce Type: cross Abstract: Human video datasets have emerged as a compelling alternative to expensive real-robot data, offering rich diversity at scale. To bridge the human-to-r

Improving 5G AI-RAN MCS Selection by Predicting Retransmissions

model-releasesarxiv-cs-ai

arXiv:2609.09324v1 Announce Type: cross Abstract: Link Adaptation (LA) in 5G NR is inherently reactive, relying on channel measurements and HARQ feedback that may become quickly obsolete when the chan

INDRA: A New AI Tool for Exploring Tobacco, Fossil Fuel, and Chemical Industry Archives

arXiv:2609.11261v1 Announce Type: cross Abstract: Five decades of litigation have disgorged hundreds of millions of pages of formerly secret business records from the tobacco industry, along with docu

safetyarxiv-cs-cl

Language-Augmented Semantic Priors for B-Spline Surface Fitting

arXiv:2609.11708v1 Announce Type: new Abstract: The use of B-splines and Non-Uniform Rational B-Splines surfaces constitutes the mathematical foundation of contemporary computer-aided design (CAD) sys

safetyarxiv-cs-cv

Learning Interaction between Image and Layout Priors for Joint Image-Layout Generation in Design Templates

arXiv:2609.11519v1 Announce Type: new Abstract: In this paper, we address the problem of graphic design template creation, which generates a background image and a layout of foreground elements over t

safetyarxiv-cs-cv

LILA: Calibration-Free Structured Pruning of Large Language Models via Latent Spectral Geometry

arXiv:2609.11163v1 Announce Type: cross Abstract: Structured pruning of large language models (LLMs) offers hardware-efficient compression, yet existing methods require calibration data, gradient comp