Search: “framework”

Image resolution enhancement for advanced semiconductor nodes

arXiv:2610.05809v1 Announce Type: new Abstract: Advanced semiconductor nodes are pushing the limits of feature sizes and require metrology with sub-nm resolution without compromising on the throughput

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Incentive Alignment in Online Experimentation

DGX agent

arXiv:2610.05922v1 Announce Type: cross Abstract: Evaluating the causal effect of new features is a central goal for online platforms. While recent literature addresses limited testing traffic via cen

safetyarxiv-cs-lg

6 Oct 2026

InterMimicGen: Scaling Humanoid Loco-Manipulation through Self-Evolving Motion Imitation

arXiv:2610.06850v1 Announce Type: cross Abstract: Captured human-object interactions provide rich supervision for humanoid loco-manipulation, but they are sparse, heterogeneous, and not directly execu

safetyarxiv-cs-cv

Local Ai

IRSTD-Agent: Agentic Infrared Small Target Detection via Zoom-Guided Interaction Learning

arXiv:2610.05342v1 Announce Type: new Abstract: Infrared small-target detection plays an important role in maritime monitoring and aerial surveillance. Although multimodal large language models (MLLMs

local-aiarxiv-cs-cv

Applications

Joint Precision Neural Networks: Task-Aware Dependency and Predictive Learning

arXiv:2610.06023v1 Announce Type: new Abstract: Exploiting meaningful latent structures from data to solve downstream tasks is a fundamental challenge in signal processing and machine learning. While

applicationsarxiv-cs-lg

Knossos and Ariadne: Benchmarking and Learning Complete Diagram Topology Extraction with Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2610.04721v1 Announce Type: new Abstract: Structural diagrams are widely used to represent complex systems and relational information across scientific, engineering, procedural, and spatial doma

Largest Rashomon sets of decision trees for robust contextual optimization

arXiv:2610.04385v1 Announce Type: cross Abstract: Many decision trees fit the same data almost equally well, yet they can route a query point to different leaves and induce different local empirical d

Local2Mesh: Spatially Localized Contour-to-Mesh for Left Ventricular Reconstruction from Sparse 2D Cardiac MRI

arXiv:2610.06052v1 Announce Type: new Abstract: Three-dimensional (3D) left ventricular (LV) reconstruction from sparse cardiac magnetic resonance (CMR) imaging remains challenging due to inter-slice

safetyarxiv-cs-cv

LocusRL: Diagnosing LLM Reward and Policy Interventions in Competitive Games

arXiv:2610.04441v1 Announce Type: new Abstract: Large language models can intervene in reinforcement learning through both reward design and action selection, yet aggregate performance offers an incom

Mapping and Classification of Trees Outside Forests using Deep Learning

arXiv:2510.25239v2 Announce Type: replace Abstract: Trees Outside Forests (TOF) play an important role in agricultural landscapes by supporting biodiversity, sequestering carbon, and regulating microc

researcharxiv-cs-cv

MemLeak: Cross-User Semantic Leakage in Multi-Tenant AI Agent Memory

arXiv:2610.04195v1 Announce Type: cross Abstract: Personal AI agents in enterprise multi-tenant deployments share a common vector store for long-term memory. Shared embedding spaces create a surface f

Local Ai

MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

arXiv:2610.06039v1 Announce Type: new Abstract: Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces lo

local-aiarxiv-cs-lg

Applications

Multimodal Deep Survival Analysis for Sinkhole Susceptibility

arXiv:2610.06365v1 Announce Type: new Abstract: Sinkholes are a widespread geohazard in karst terrain. In Florida, soluble carbonate bedrock, shallow groundwater, and intense rainfall combine to make

applicationsarxiv-cs-lg

Local Ai

Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

arXiv:2610.04545v1 Announce Type: cross Abstract: This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributi

local-aiarxiv-cs-ro

On the Approximation Relationship between Optimizing Ratio of Submodular (RS) and Difference of Submodular (DS) Functions

arXiv:2101.01631v2 Announce Type: cross Abstract: We demonstrate that from an algorithm guaranteeing an approximation factor for the ratio of submodular (RS) optimization problem, we can build another

Optimizing Breast Cancer Detection in Mammograms: A Comprehensive Study of Transfer Learning, Resolution Reduction, and Multi-View Classification

arXiv:2503.19945v4 Announce Type: replace-cross Abstract: Mammography, an X-ray-based imaging technique, remains central to the early detection of breast cancer. Recent advances in artificial intellig

tutorialsarxiv-cs-cv

Pessimistic Minimax Learning for Public-Private Information Games under Unilateral Coverage

arXiv:2610.04997v1 Announce Type: new Abstract: We study offline learning in two-player zero-sum contextual games with public and private information, motivated by strategic settings such as auctions

Physics-Informed but Not Physics-Consistent: Error Geometry and Subspace Projection for Neural AC Power Flow

arXiv:2610.05959v1 Announce Type: new Abstract: Recent neural power-flow solvers, including emerging foundation models, achieve accurate voltage predictions, yet such accuracy does not necessarily imp

Physics Residual Dynamics and Reduced Order Whole-Body Planning for Obstacle Aware Human Robot Cloth CoTransportation

arXiv:2610.06641v1 Announce Type: new Abstract: Human--robot co-transportation of deformable objects requires predicting object deformation during motion, since obstacle clearance depends on both the

researcharxiv-cs-ro

Priced Guidance: Can Language Models Generate Future Research Ideas?

arXiv:2610.04976v1 Announce Type: new Abstract: We evaluate language models' capability to generate novel research ideas through the lens of compression. We aim to lower-bound the potentially tiny pro

Private Component-by-Component Learning

arXiv:2610.05102v1 Announce Type: new Abstract: We study differentially private learning problems in the realizable setting, where a hypothesis is specified by k components. A direct iteration of priv

Probability flow ODEs in score-based and reflected diffusion models

arXiv:2610.03846v1 Announce Type: cross Abstract: Probability-flow ordinary differential equations (PF-ODEs) are widely used as deterministic samplers for score-based diffusion models. Their usual jus

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

Recon2Servo: Robotic Ultrasound Visual Servoing via Learned Image-to-Motion Inference

arXiv:2610.06010v1 Announce Type: new Abstract: Ultrasound visual servoing is essential for autonomous robotic ultrasound, yet 6-DoF probe control from 2D B-mode images remains challenging due to limi

safetyarxiv-cs-ro

Reflections and Fragments: Securing LLMs Against Sequential Mosaic Attacks

arXiv:2610.05346v1 Announce Type: new Abstract: Self-play red-teaming improves language-model safety by pitting attacker and defender roles against each other in a zero-sum game. However, real adversa

Representation-Aligned Auxiliary Supervision for Language Model Adaptation

arXiv:2610.04098v1 Announce Type: cross Abstract: Language models exhibit strong reasoning capabilities, yet adapting them to structured domains remains challenging and can yield inconsistent outcomes

Resisting Adversarial Attacks in Deep Neural Networks using Diverse Decision Boundaries

arXiv:2208.08697v2 Announce Type: replace-cross Abstract: The security of deep learning (DL) systems is an extremely important field of study as they are being deployed in several applications due to

researcharxiv-cs-cv

Hardware

RESOLVE: Language-Agnostic Validation of GPU Kernels Through Testing, Reduction, and Proof

arXiv:2610.05683v1 Announce Type: cross Abstract: AI systems can now write and optimize production GPU kernels, but validating them remains an important challenge. Evaluating the kernel on a few rando

hardwarearxiv-cs-lg

Robotic Long-Horizon Manipulation with Progressive In-Context Code Generation and Episodic Feedback

arXiv:2503.21969v4 Announce Type: replace Abstract: Robotic long-horizon manipulation requires robots to compose perception, reasoning, and action over extended task sequences, yet existing language-c

tutorialsarxiv-cs-ro

Rotated, but How Far? Diagnosing and Improving Object-Rotation Reasoning in VLMs

model-releasesarxiv-cs-cv

arXiv:2610.05715v1 Announce Type: new Abstract: Vision-language models (VLMs) can detect that an object has rotated across views, but cannot reliably tell by how much. We introduce OR-Bench, a fine-gr

SALUS: Automated Auditing of NL-to-SQL Benchmarks through Weak Supervision of Multi-Agent Output

arXiv:2610.05540v1 Announce Type: cross Abstract: Natural language to SQL (NL-to-SQL) benchmarks are foundational to progress in data analysis research, yet recent work has shown that widely-used benc

Scenario-Based Compositional Statistical Model Checking for Safety Specifications

arXiv:2610.05571v1 Announce Type: cross Abstract: In safety-critical domains such as autonomous driving, systems must be evaluated across a large number of environment conditions, often represented as

safetyarxiv-cs-ro

Score-Calibrated Flow for Sampling from Unnormalized Densities with Applications to Generative Online Reinforcement Learning

arXiv:2610.04696v1 Announce Type: new Abstract: Diffusion and flow models provide expressive policy classes for online reinforcement learning (RL), enabling multimodal behaviors and improved performan

SimAuthor: Harnessing Foundation Models for Persistent Scientific Simulator Authoring

arXiv:2610.06257v1 Announce Type: new Abstract: Foundation models can generate scientific code, but authoring a scientific simulator (an executable program encoding hypotheses about how mechanisms gen

tutorialsarxiv-cs-lg

Spacecraft Rendezvous Trajectory Generation with Modular Constraints via Diffusion Model Composition

arXiv:2610.05642v1 Announce Type: cross Abstract: Emerging mission classes such as on-orbit servicing, satellite inspection, and active debris removal require trajectory design methods that are adapta

Spectral Geometry of Attention: From Information Routing to Uncertainty

arXiv:2610.06012v1 Announce Type: new Abstract: In this work, we study transformer attention through the lens of spectral geometry and operator theory. We view each attention head as a functional map

Stability and Generalization of Stochastic Nonconvex Optimization under Heavy-Tailed Noise: From Gradient Norm to Goldstein Stationarity

arXiv:2601.19730v2 Announce Type: replace Abstract: The empirical evidence indicates that stochastic optimization with heavy-tailed gradient noise is more appropriate to characterize the training of m

Applications

Structural Foundations of Nonlinear Systems with Unknown Inputs: The UID-Induced Normal Form and Minimal-Sensing Structure-from-Motion

arXiv:2610.05939v1 Announce Type: cross Abstract: This paper establishes the first general structural solution to the problem of state estimation for nonlinear systems driven by unknown inputs. Buildi

applicationsarxiv-cs-cv

Structured Neural Modeling of Daily Arctic Sea-Ice Concentration Evolution: Physical-Trajectory-Driven Learning and Forecast-Domain Adaptation

arXiv:2610.03743v1 Announce Type: cross Abstract: Accurate modeling of the daily evolution of sea ice concentration (SIC) is central to improving the credibility and operational forecasting capability

The Effect of Missingness-Pattern Mismatch on Method Selection for Time-Series Classification: A Controlled Empirical Study

arXiv:2610.05368v1 Announce Type: new Abstract: Classifiers for time-series classification are commonly selected on validation data, but the temporal pattern of missing observations at deployment may

Toward Reliable Infant Pose Estimation: A Training-Dynamics Approach to Noisy Annotation Detection

model-releasesarxiv-cs-cv

arXiv:2610.06423v1 Announce Type: new Abstract: Spontaneous movement analysis in preterm infants relies increasingly on markerless pose estimation (PE) to derive clinically relevant motion biomarkers

Towards Safer Autonomous Driving in an Open World: A Dual-Process Approach

arXiv:2610.04088v1 Announce Type: cross Abstract: Before autonomous driving systems can be deployed on public roads, it is vital that these systems comply with safety standards, traffic rules, and soc

safetyarxiv-cs-ro

Trust the View That Sees the Target: Mining Cross-View Conflicts for Reliability-Gated Disaster Damage Assessment

arXiv:2610.04327v1 Announce Type: new Abstract: After a disaster, building damage is assessed from overhead tiles and ground-level photographs, and most methods fuse the two views symmetrically, trust

researcharxiv-cs-cv

VERA: Verdict-Conditioned Reliability for Adaptive LLM Judges

arXiv:2610.05452v1 Announce Type: new Abstract: Accurately estimating judgment reliability is a central challenge in adapting LLM judges to newly verified feedback while preserving previously learned

vMF Sentence LDA: A Spherical Topic Model over Sentence Embeddings

arXiv:2610.05095v1 Announce Type: cross Abstract: Latent Dirichlet Allocation (LDA) and models derived from it remain widely used topic models. LDA observes each document as a bag-of-words and models

WaveGSSM: Graph Wave State Space Models for Propagating Spatio-Temporal Patterns

arXiv:2610.06540v1 Announce Type: new Abstract: Spatio-temporal graph models typically encode each snapshot with a GNN and then connect the resulting representations through a temporal module. This sp

Your Unlearning Gives You Away: Identifying Erased Concepts in Diffusion Models

arXiv:2610.05601v1 Announce Type: new Abstract: Existing attacks on unlearned diffusion models assume that the erased concepts are known in advance and focus on recovering them. In practice, however,

AMBER: Multi-View Adaptive Budget Allocation for Listwise Vision-Language Reranking