Search: “framework”

ScalLoc: Continuous Oblique Thermal UAV Geo-Localization with a 2D Satellite Map

arXiv:2610.14866v1 Announce Type: new Abstract: Cross-modal Thermal Geo-localization (TG) provides an illumination-robust positioning solution for Unmanned Aerial Vehicles (UAVs) in Global Navigation

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Safety

Sequent-Prover: Training Agents for Formal, Checkable SMT-based Reasoning

DGX agent

arXiv:2610.15258v1 Announce Type: cross Abstract: We introduce Sequent-Prover, a family of verifier-using language-model agents, and the post-training framework that produces them. Agents reason in an

safetyarxiv-cs-lg

14 Oct 2026

Tutorials

Structural Pass Analysis in Football: Learning Pass Archetypes and Tactical Impact from Spatio-Temporal Tracking Data

arXiv:2603.28916v2 Announce Type: replace Abstract: Football action-value approaches estimate scoring, possession, or other downstream outcome value; complementary descriptions can characterise how a

tutorialsarxiv-cs-lg

Task-Space Motion-Force Nonlinear Model Predictive Control for Precise and Compliant Control under Uncertainties

arXiv:2610.17069v1 Announce Type: new Abstract: In Nonlinear Model Predictive Control (NMPC), the control law is implicitly determined by the solution of an Optimal Control Problem (OCP). Consequently

researcharxiv-cs-ro

Text-Guided Medical Image Segmentation via Residual Aggregation and Dense Alignment Representations

model-releasesarxiv-cs-cv

arXiv:2610.14944v1 Announce Type: new Abstract: Specifying segmentation targets with natural language provides flexible semantic conditioning for medical image segmentation. However, existing methods

The Tokens Strike Back: Safety-Aware Denoising with Directional Embedding-based Revision

arXiv:2610.17636v1 Announce Type: new Abstract: The Safety-Aware Denoiser (SAD) is a recent, training-free, safety-guidance framework for text diffusion models. During inference, SAD steers text sampl

safetyarxiv-cs-lg

ToF-Wheel Odometry: Navigating Degeneration of Localization With Limited Sensing Capabilities

arXiv:2610.14590v1 Announce Type: cross Abstract: Wheel odometry provides an efficient motion prior for ground robots but is prone to transient violations such as wheel slip or terrain-induced tilt. I

UMAS3D: Unified Mask-Free 3D Editing with Region-Adaptive Source Preservation

arXiv:2610.15533v1 Announce Type: new Abstract: 3D editing aims to modify an existing 3D asset according to user intent while preserving geometry and appearance outside the intended edit region. Exist

Uncertainty Evaluation: Bridging Machine Learning and Measurement Science

arXiv:2610.18066v1 Announce Type: new Abstract: Reliable uncertainty evaluation is essential for assessing the trustworthiness of machine learning (ML) predictions, particularly in safety-critical app

safetyarxiv-cs-lg

Unravel: Recovering an Interactive 3D Scene from a Single Image

arXiv:2610.16146v1 Announce Type: new Abstract: We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable a

agentsarxiv-cs-cv

Applications

ViewStruct: View-Grounded Articulation and Connectivity Inference

arXiv:2610.16793v1 Announce Type: new Abstract: Interacting with unfamiliar objects requires understanding how their parts connect and move. We introduce ViewStruct, a framework for jointly predicting

applicationsarxiv-cs-cv

Walk Like This: Stylized Locomotion for Physics-Based Characters through Example-Driven Diffusion

arXiv:2610.18147v1 Announce Type: new Abstract: We present a real-time framework for expressive legged locomotion that enables independent control over velocity and style. Unlike existing data-driven

researcharxiv-cs-ro

When Trackers Fail: VLM-Guided Verification and Recovery for Robust Video Object Segmentation

arXiv:2610.15929v1 Announce Type: new Abstract: Recent trackers built on foundation models such as the Segment Anything Model (SAM) achieve strong performance by propagating object masks through memor

agentsarxiv-cs-cv

World2TS: Real-World Event Context for Time-Series Forecasting

arXiv:2610.14861v1 Announce Type: new Abstract: Time-series forecasting plays a vital role in a wide range of real-world applications. Recent approaches have achieved strong performance by modeling te

agentsarxiv-cs-lg

Agent4Spec: An LLM-based Agentic System to Optimize API Specifications through Automated Validation and Market Analysis

arXiv:2610.13273v1 Announce Type: cross Abstract: API specifications serve as critical documentation for modern software development, directly impacting integration efficiency and client code generati

agentsarxiv-cs-ai

Algebraic Integer Quantization for Machine Learning Applications

model-releasesarxiv-cs-lg

arXiv:2610.12494v1 Announce Type: new Abstract: In this article, we propose algebraic integer number formats (AINF) as a framework for highly configurable and accurate compressed computation. A key pr

Approximation of differential entropy in Bayesian optimal experimental design

arXiv:2510.00734v2 Announce Type: replace-cross Abstract: Bayesian optimal experimental design provides a principled framework for selecting experimental configurations that maximize obtained informat

AutoControl Arena: Synthesizing Executable Test Environments for Frontier AI Risk Evaluation

arXiv:2603.07427v3 Announce Type: replace Abstract: As Large Language Models (LLMs) evolve into autonomous agents, existing safety evaluations face a fundamental trade-off: manual benchmarks are costl

safetyarxiv-cs-ai

Coordinate-Free Automatic Differentiation

arXiv:2610.12776v1 Announce Type: new Abstract: Automatic differentiation (AD) is a cornerstone of modern machine learning. Since all AD frameworks implicitly fix a basis of Euclidean space to define

Evo-World: A Lightweight Vision-Language-Action Model with Future Motion Prediction via Optical-Flow Supervision

arXiv:2610.12936v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide a unified framework for visual understanding, language grounding, and robot control, yet anticipating how th

safetyarxiv-cs-ro

Evo^2: Evolving the Evolver through Weight-Harness Co-Evolution

model-releasesarxiv-cs-cl

arXiv:2610.13025v1 Announce Type: new Abstract: Self-evolving agents are increasingly used to improve language model systems without human intervention through either weight updates or harness improve

Faithful and Complete LLM-Assisted Automated Construction of Hierarchical Hardware Knowledge Graphs

model-releasesarxiv-cs-ai

arXiv:2610.12762v1 Announce Type: new Abstract: Hardware datasheets contain engineering specifications essential for component selection, system integration, and hardware compatibility verification. H

HorizonNav: Geometry-Guided Video Diffusion for Anticipatory 3D Robot Navigation

arXiv:2610.13849v1 Announce Type: new Abstract: We present HorizonNav, a video diffusion-based framework for anticipatory robot navigation that transforms a single RGB image and a text prompt into a g

safetyarxiv-cs-ro

Humanize Olympiad Agents: A Multi-Session Workflow for Olympiad Problem Solving with Solve, Review, Wiki, Verify

model-releasesarxiv-cs-ai

arXiv:2610.13632v1 Announce Type: new Abstract: Large language model (LLM) agents are rapidly improving on long-horizon scientific and olympiad tasks. Recent systems have produced a Lean-formalized re

Hyper Algorithm Design Agent: Evolving Learnable Optimizer from Zero

arXiv:2609.35328v2 Announce Type: replace Abstract: Meta-Black-Box Optimization (MetaBBO) is one of the highlights in the recent AI for Optimization trend. This paradigm's bi-level workflow leverages

safetyarxiv-cs-ai

Learning by Compression: Risk Estimates Attain the Law-of-Large-Numbers Rate

arXiv:2610.13442v1 Announce Type: cross Abstract: Compression schemes provide a general framework for deriving data-dependent risk bounds for learning algorithms. For learning rules based on preferent

MoPrO-SD: Modular Prompt Optimization for Stance Detection

model-releasesarxiv-cs-cl

arXiv:2610.13386v1 Announce Type: new Abstract: Stance detection remains challenging for large language models (LLMs) due to implicit opinions, sarcasm, and context-dependent expressions of stance. Al

MORAD: Reinforcement Learning with Multi-Objective Rewards for RNA Inverse Design

arXiv:2610.13305v1 Announce Type: new Abstract: We introduce MORAD, an online reinforcement learning framework for backbone-conditioned RNA diffusion models that trains a single shared policy across d

safetyarxiv-cs-lg

NV-Tesseract-AD: Curriculum-Enhanced Conditional Diffusion for Multivariate Time-Series Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2610.12754v1 Announce Type: new Abstract: We propose NV-Tesseract-AD, a curriculum learning-enhanced conditional diffusion framework for multivariate time-series anomaly detection. Our central h

Temporal Evidence Forests for Long-Horizon Multi-Party Conversational Memory

model-releasesarxiv-cs-cl

arXiv:2610.12874v1 Announce Type: new Abstract: Long-term memory has been widely adopted in LLM-based agents to support persistent interaction and personalized assistance. Long-term multi-party intera

Tensor-based Fusion of Multi-modal Data for Predicting Cancer Risk Levels

arXiv:2610.13221v1 Announce Type: new Abstract: Cancer diagnosis and treatment increasingly rely on multi-modal diagnostic technologies that generate high-dimensional datasets. Although these datasets

Time Delay System for Sequence Modeling

arXiv:2610.12864v1 Announce Type: new Abstract: Existing sequence models share a critical limitation: they lack an explicit, interpretable mechanism for content-aware temporal recall. LSTMs compress e

researcharxiv-cs-cl

VETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning

model-releasesarxiv-cs-ai

arXiv:2610.13098v1 Announce Type: new Abstract: Visual agents for symbolic graphics reasoning depend on executable world representations, yet continued improvement remains bottlenecked by ambiguous su

X-AgentRed: Red-Teaming Personal Agents in Evolving Multi-Service Ecosystems

arXiv:2610.13886v1 Announce Type: new Abstract: Personal agents increasingly connect to services across the web and applications by using tools. As the effects of their actions accumulate and interact

agentsarxiv-cs-ai

Applications

AdaSwitch: An Adaptive Switching Meta-Algorithm for Learning-Augmented Bounded-Influence Problems

arXiv:2509.02302v2 Announce Type: replace Abstract: We study history-dependent online problems with a possibly inaccurate prediction of the future request sequence. Motivated by several real-world app

applicationsarxiv-cs-lg

AgentFly: Scaling Agentic Reinforcement Learning with Unified Resource System

arXiv:2507.14897v2 Announce Type: replace Abstract: Methods to build LLM agents have evolved from prompt engineering and supervised finetuning to agentic reinforcement learning (agentic RL). However,

agentsarxiv-cs-ai

Tutorials

Ambient Discrete Diffusion: Using the Wrong Data at the Right Time for Data Efficient Learning

arXiv:2610.12340v1 Announce Type: new Abstract: We introduce RefineMix, a framework for training discrete diffusion models under severe data scarcity, a common constraint in scientific applications. R

tutorialsarxiv-cs-lg

An Efficient Quantum Circuit for Flow Model Execution Using Quantum Neural Networks

arXiv:2610.11537v1 Announce Type: cross Abstract: Flow models generate trajectories from an initial distribution to a target distribution by solving an ordinary differential equation defined by a velo

Barron Optimal Transport I: Generative Modeling

arXiv:2610.10875v1 Announce Type: new Abstract: Motivated by recent applications in generative modeling and sampling, we introduce a framework for optimal measure transport where cost captures the not

Best of Both Worlds in Federated LSA: Speedup When Possible, Personalization Always

arXiv:2610.11555v1 Announce Type: new Abstract: We study personalized federated linear stochastic approximation (LSA), a framework which notably encompass personalized temporal difference learning. In

agentsarxiv-cs-lg

Tutorials

Bilevel optimization for data-driven learning of Koopman embeddings using kernel-based autoencoders

arXiv:2610.12370v1 Announce Type: new Abstract: Koopman operator theory provides a linear framework for analyzing nonlinear dynamical systems and has become a major tool for data-driven modeling. A ce

tutorialsarxiv-cs-lg

Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy

arXiv:2610.11222v1 Announce Type: cross Abstract: Preclinical models poorly predict human drug efficacy, particularly in neurological disorders. Neural activity offers a uniquely rich source of transl

DAMP: Humanoid Locomotion via Denoised Belief Learning and Adversarial Motion Priors

arXiv:2610.11505v1 Announce Type: new Abstract: Humanoid robots possess the structural capability to traverse complex terrains. However, achieving stable t raversal without relying on perceived inform

safetyarxiv-cs-ro

Equal Path Cost, Unequal Output Effects: Understanding Perturbation Propagation in Diffusion Models

arXiv:2610.11380v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in generative modeling, with their sampling procedures routinely modified to control generation and im

researcharxiv-cs-ai

Fluid-Gen-Zero: Grounding Pretrained Video Generators in Physics without Training

model-releasesarxiv-cs-cv

arXiv:2610.10984v1 Announce Type: new Abstract: We present Fluid-Gen-Zero, a training-free framework for physics-aware fluid-object interaction video generation that decouples physical reasoning from

Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size

arXiv:2510.04440v2 Announce Type: replace Abstract: We develop a source-driven fractional heat-kernel framework for semi-super-vised graph learning that combines nonlocal propagation with sustained la

Fresco++: Frequency-Guided and Canonical-Consistent Optimization for Fine-Grained Head Avatar Modeling

arXiv:2610.11412v1 Announce Type: new Abstract: We propose Fresco++, a unified optimization framework for fine-grained and view-consistent head avatar reconstruction. Head avatar optimization is typic

From Language to Motion: Task-Conditioned Focal-Stack Trajectory Integration for Microscopic Robots

arXiv:2610.12241v1 Announce Type: new Abstract: Microscopic robots require accurate task geometry despite changes in language, parts, and focus. We present a semantic-to-physical framework that maps i

researcharxiv-cs-ro