Search: “models”

Certification of Real Images through Calibrated Content Authentication

arXiv:2610.05870v1 Announce Type: new Abstract: Generative models can synthesize high-quality inauthentic multimedia content that is already being misused at scale. We evaluate twenty deepfake detecto

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Research

Consideration Circuits: Depth Separation and Universality Beyond a Single Softmax

DGX agent

arXiv:2610.04143v1 Announce Type: new Abstract: Most feature-based choice models, classical and deep, score items and apply a single softmax. We introduce consideration circuits (CC), feature-based mo

researcharxiv-cs-lg

6 Oct 2026

Continual Action Quality Assessment via Adaptive Manifold-Aligned Graph Regularization

arXiv:2510.06842v2 Announce Type: replace Abstract: Action Quality Assessment (AQA) quantifies human actions in videos, supporting applications in sports scoring, rehabilitation, and skill evaluation.

D-DOIT: Training-free Adaptation of Discrete Diffusion via Doob's h-Transform

arXiv:2610.04938v1 Announce Type: new Abstract: We propose D-DOIT (Discrete Doob-Oriented Inference-time Transformation), a training-free and efficient adaptation method for discrete diffusion models

Deep Learning Denoising of Real SWOT Sea Surface Height Observations

arXiv:2610.03739v1 Announce Type: cross Abstract: The SWOT (Surface Water Ocean Topography) mission is currently providing unpreceded high-resolution measurements of Sea Surface Height (SSH), revealin

Distribution Matching Evolutionary Algorithms for Rare Event Sampling

arXiv:2610.03833v1 Announce Type: cross Abstract: A novel discovery is one which is both useful and surprising: a generative model's output is a useful discovery if it has a low probability of being g

Applications

Dual-Scale Relational Graph Transformers for Ecosystem-Aware Fraud Detection

arXiv:2610.04138v1 Announce Type: new Abstract: Account takeover (ATO) fraud is a growing threat to digital banking, requiring effective detection while minimizing friction for legitimate customers. P

applicationsarxiv-cs-lg

Environmental sensor readings in two crop disease image datasets identify the session in which each image was taken

arXiv:2610.06369v1 Announce Type: new Abstract: Integrating environmental sensor data with leaf imagery is widely reported to boost crop disease classification accuracy. In this work, we reveal that t

Errors of LLM-Assisted Literature Retrieval in Environmental Science: A Comparison Study of Abstract versus Full-text Based Prompts

arXiv:2610.05690v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for literature search and synthesis. However, it is unclear whether they retrieve accurate bibliogr

EXHIB: A Benchmark for Realistic and Diverse Evaluation of Function Similarity in the Wild

arXiv:2604.01554v2 Announce Type: replace-cross Abstract: Binary Function Similarity Detection (BFSD) is a core problem in software security, supporting tasks such as vulnerability analysis, malware c

First-Order Steering: Translating Weight Adaptation into Activation Steering

arXiv:2610.04283v1 Announce Type: new Abstract: Activation steering exploits interpretable directions in the residual stream to enable inference-time manipulation of model behavior. Composing steering

FTD-GNO: Memory-Efficient Graph Neural Operators through Functional Tensor Decomposition of the Kernel

arXiv:2610.04212v1 Announce Type: new Abstract: Graph Neural Operators (GNOs) provide flexible surrogate models for learning solution operators of partial differential equations (PDEs). However, stand

Inspect Robots: Evaluating the Capabilities and Safety of Embodied AI

arXiv:2610.06306v1 Announce Type: new Abstract: General purpose language models are increasingly able to control robotic hardware. Understanding the capabilities and safety of these models when embodi

safetyarxiv-cs-ro

Applications

KESurv: A Kernel Ensemble Method for Patient-Specific Survival Prediction

arXiv:2610.06434v1 Announce Type: cross Abstract: Predicting patient-specific survival functions is crucial for clinicians in making informed decisions about patient care and treatment strategies. Amo

applicationsarxiv-cs-lg

Latent Safety Filters: When a Lossy Encoder Admits a Transferable Certificate

arXiv:2610.04297v1 Announce Type: cross Abstract: Latent safety filters certify safety on a learned low-dimensional representation of the state, enabling constraints that resist analytic description.

LiFT: Loop Flow Transformers

arXiv:2610.05538v1 Announce Type: new Abstract: We introduce Loop Flow Transformers (LiFT), a family of looped generative models that scales computation by repeatedly applying a shared Diffusion Trans

OGAM: Connecting Systematic Testing to Runtime Assurance through Object-Grounded Attention Monitoring for VLA Policies

arXiv:2610.05878v1 Announce Type: new Abstract: Benchmarks expose vision-language-action (VLA) policies to few canonical instructions, while exhaustive deployment testing is impossible. We introduce O

Path Laplacian Encodings for Directed Graphs

arXiv:2610.04657v1 Announce Type: new Abstract: Directed graphs naturally model many real-world systems in which interactions are asymmetric, such as citation networks, web graphs, and information-flo

Probabilistic Pedestrian Forecasts from a Handheld Phone: World-Frame Heat Maps, Visual-Inertial Height Drift, and Evaluation without Ground Truth

arXiv:2610.04736v1 Announce Type: new Abstract: A pedestrian with a phone could be shown where nearby people will be in the next few seconds, if the forecast stays on the ground while the phone moves,

Tutorials

Progressive Multi-Ancestor Bit-Depth Distillation

arXiv:2610.04100v1 Announce Type: new Abstract: Model compression strategies are widely employed to reduce memory footprint and network complexity, particularly for devices with constrained computatio

tutorialsarxiv-cs-lg

Propagating Elevation-Map Uncertainty Through the Contact Maximum in Closed Form

model-releasesarxiv-cs-ro

arXiv:2610.06103v1 Announce Type: new Abstract: Risk-aware planners score paths on uncertain elevation maps using the path cost's mean and standard deviation. Modeling rigid contact, however, requires

ReMaD: Tuning-free Domain Adaptation for Classification and Out-of-Distribution Detection

arXiv:2610.05718v1 Announce Type: new Abstract: We introduce Reduced-rank Mahalanobis Distance (ReMaD), a novel prototypical distance-based refinement to classification and out-of-distribution (OOD) d

RMMBench: A Comprehensive Benchmark for Robotic Mobile Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.05414v1 Announce Type: new Abstract: Although the advancement of vision-language models (VLMs) has endowed robots with enhanced environmental understanding and task reasoning, a comprehensi

Local Ai

Robust Ensemble Guidance for Scientific Inverse Problems

arXiv:2610.05371v1 Announce Type: new Abstract: Ensemble guidance combines pretrained diffusion priors with black-box forward models to solve inverse problems without differentiating through the physi

local-aiarxiv-cs-lg

Agents

SelectOccFlow: Selective Spatiotemporal Aggregation for 3D Occupancy and Scene Flow Prediction

arXiv:2610.04356v1 Announce Type: new Abstract: Comprehensive 3D scene understanding for autonomous driving requires modeling geometry, semantics, and motion. However, camera-based occupancy and scene

agentsarxiv-cs-cv

SemCam: Semantic Camera Motion Control for Video Generation

arXiv:2610.05141v1 Announce Type: new Abstract: Controlling the camera relative to a moving subject in an existing video is challenging: behaviors such as maintaining a frontal view require the camera

Singular parameters and missing limits in neural PDE solvers

arXiv:2610.06770v1 Announce Type: cross Abstract: Neural solvers for partial differential equations (PDEs) can approach an accurate solution while their parameters grow without bound. In such cases, t

SkillScriptBench: Benchmarking Self-Evolution of Executable Agent Skill Packages Beyond Markdown

arXiv:2610.04008v1 Announce Type: cross Abstract: Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing err

StagQ: Constraint-Driven Multi-Precision Weight Quantization for LLMs

arXiv:2610.05977v1 Announce Type: new Abstract: Serving a large language model (LLM) across a fleet of deployments requires several weight-precision operating points. Multi-precision formats serve the

Target-free Latent Safety Alignment

arXiv:2610.04467v1 Announce Type: new Abstract: Large language models (LLMs) remain highly vulnerable to jailbreak attacks that induce harmful behaviors and circumvent safety alignment. To defend agai

Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLA

arXiv:2610.05025v1 Announce Type: new Abstract: Dual-system Vision-Language-Action (VLA) models improve real-time robotic control by pairing a slow, reasoning-capable generalist with a fast specialist

researcharxiv-cs-cv

UnAct: Gradient-Free Unlearning via Targeted Activation Intervention

arXiv:2610.04426v1 Announce Type: cross Abstract: Machine unlearning seeks to remove the influence of designated training data from a trained model without retraining from scratch. Retrain-free method

What to Preserve in Recursive Computation: A Local Predictive Sufficiency Principle

arXiv:2610.04303v1 Announce Type: new Abstract: Recursive computation repeatedly compresses or reuses intermediate states, creating a simple tension: information that must remain useful across longer

When Does Longer Reasoning Help? Predicting Mathematical Reasoning Through Discovery and Execution

arXiv:2610.05322v1 Announce Type: new Abstract: Test-time compute can improve mathematical reasoning, but can short-budget runs predict how mathematical reasoning scales with additional compute? We in

Which Preferences to Train On? End-to-End Multi-Objective Alignment with an Adversarial Preference Distribution

arXiv:2610.04845v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human values is important for safe, efficient, and beneficial AI deployment. However, human values are multif

WILLIE: A Unified Framework and Benchmark for Wound Classification, Segmentation, and Localization

arXiv:2610.05341v1 Announce Type: new Abstract: Chronic wound management affects over 8.2 million patients in the United States and imposes substantial clinical and economic burden. Clinical wound ass

Local Ai

A Locally Penalized Cross-Estimate Federated Method with Guarantees for Constrained Personalized Learning

arXiv:2603.19617v2 Announce Type: replace Abstract: Federated learning (FL) is a communication-efficient framework for solving distributed optimization problems. Standard FL methods aggregate local up

local-aiarxiv-cs-lg

Ask, Relax, or Act? Evaluating Actionable Indeterminacy in LLM Preference Reasoning

model-releasesarxiv-cs-ai

arXiv:2610.03102v1 Announce Type: cross Abstract: An LLM agent can recognize uncertainty yet still choose the wrong next step: asking when action is already justified, or seeking clarification when th

Automatic Evaluation of Mental Health Stigma in Online Communication

model-releasesarxiv-cs-cl

arXiv:2610.02775v1 Announce Type: new Abstract: Mental health stigma has profoundly harmful impacts but its complexity makes it difficult to evaluate. Stigma may involve explicit derogation, but also

Behavior Pack Optimization for Video MLLM Post-Training

arXiv:2610.03141v1 Announce Type: new Abstract: Video multimodal large language models (MLLMs) keep climbing video question answering benchmarks, yet shuffling the frames, masking the segment that sup

researcharxiv-cs-cv

Local Ai

Bridging Frontier Reasoning and Robot Execution: From Autonomous Demonstration Generation to Dense Language Supervision

arXiv:2610.03615v1 Announce Type: new Abstract: Recent advances in frontier models enable robot manipulation from only a few demonstrations, but high inference latency limits their use for real-time r

local-aiarxiv-cs-ro

Characterizing the Performance Gap in Human Activity Recognition for Older Adults

arXiv:2610.02711v1 Announce Type: cross Abstract: Human activity recognition (HAR) from wrist-worn accelerometers is increasingly used for health and behavioral tracking. Yet, most wearable HAR models

Agents

Coherence-Driven Belief Formation and Population Dynamics of Contagion in LLM Agents

arXiv:2610.02654v1 Announce Type: new Abstract: Models of social contagion usually assume how individuals adopt beliefs and derive population behavior from it. We instead empirically measure belief ad

agentsarxiv-cs-ai

DAWIS: Data Assimilation with Windowed Inverse Sampling via Multitask Interpolants

arXiv:2610.03314v1 Announce Type: cross Abstract: Flow- and diffusion-based generative models have recently emerged as flexible and highly efficient forecasting models for dynamical systems. When comb

DeepStratNet: A Context-Aware Coordinate Regression Framework for Seismic Horizon Tracking under Sparse Labels

arXiv:2610.02494v1 Announce Type: new Abstract: Automatic horizon tracking is a foundational task in 3D seismic interpretation. Most existing deep learning approaches formulate it as dense semantic se

researcharxiv-cs-cv

Applications

Dual-Context Analog Retrieval for Time Series Forecasting

arXiv:2610.03491v1 Announce Type: new Abstract: Most long-term time-series forecasting models map the look-back window directly to the full horizon in a single pass. While efficient, this design does

applicationsarxiv-cs-lg

DyadMem: A Long-Term Memory Benchmark of How Agents Work with Users

model-releasesarxiv-cs-ai

arXiv:2610.03020v1 Announce Type: new Abstract: Long-term agents must remember not only what is true about a user, but also how a particular agent should work with that user as their shared history ev

Agents

Dynamic Expert Pruning for Multi-Agent Systems

arXiv:2610.02951v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures scale language models efficiently by activating only a few experts per token, but the saving is confined to com

agentsarxiv-cs-ai