Search: “framework”

EviRec: Continual Evidence Learning for Dual Cold-Start POI Recommendation

arXiv:2609.20313v1 Announce Type: new Abstract: Point-of-Interest (POI) recommendation is a core task in location-based services, yet most existing methods assume a fixed user population and POI catal

researcharxiv-cs-lg

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Research

Expected Hypervolume Maximization for Multiobjective Optimization under Uncertainties

DGX agent

arXiv:2609.19858v1 Announce Type: new Abstract: The problem of multiobjective optimization under uncertainties is often approached by taking the expectation of each objective. In this work, we propose

researcharxiv-cs-lg

18 Sept 2026

Exploring Sparsity and Smoothness of Arbitrary Lp Norms in Adversarial Attacks

arXiv:2602.06578v2 Announce Type: replace-cross Abstract: Adversarial attacks against deep neural networks are commonly constructed under ell_p norm constraints, most often using p=1, p=2 or p=infty,

FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender System

arXiv:2609.20175v1 Announce Type: cross Abstract: The filter bubble is a notorious issue in Recommender Systems (RSs), which describes the phenomenon whereby users are exposed to a limited and narrow

FakeSpotter: A content and strategy agnostic Viral Misinformation Detection Tool

arXiv:2609.19152v1 Announce Type: new Abstract: Misinformation detection tools often rely on binary true and false classifications or models trained on historical examples, limiting their usefulness w

researcharxiv-cs-cl

Hardware

Fast Cross-Strength Multi-Contrast Brain MRI Translation using Latent Bridge Matching

arXiv:2609.20341v1 Announce Type: new Abstract: Magnetic Resonance Imaging (MRI) acquired at different field strengths exhibits pronounced variation in noise, resolution, homogeneity, and contrast, wh

hardwarearxiv-cs-cv

FedeRICo: Federated Region-Influenced Coupling for Traffic Flow Prediction

arXiv:2609.20026v1 Announce Type: new Abstract: Urban traffic forecasting often relies on information distributed across stakeholders who may be unable to share raw data due to privacy or commercial c

FedFIbOS: Fisher Importance based Optimal Submodelling for Heterogeneous Federated Learning

model-releasesarxiv-cs-lg

arXiv:2609.19559v1 Announce Type: new Abstract: Heterogeneous federated learning requires clients with diverse computational capacities to collaboratively train a global model, where each client train

FedVideoMAE: Efficient Federated Video Moderation with Differential Privacy and Secure Aggregation

arXiv:2512.18809v3 Announce Type: replace-cross Abstract: Short-form video moderation is increasingly pushed toward edge and privacy-sensitive settings, where users may intend videos for a limited aud

Tutorials

FlipToSee: A Probabilistic Stable Placement Prior for Active Visual Exploration via Regrasping

arXiv:2609.20078v1 Announce Type: new Abstract: Active visual exploration of tabletop objects often requires reorienting an unknown resting object onto a different stable support face to expose occlud

tutorialsarxiv-cs-ro

FlowSGS: Improving Flow Matching Priors for Inverse Imaging with Stochastic Interpolants

arXiv:2609.20769v1 Announce Type: new Abstract: Flow matching has emerged as the state-of-the-art generative model and has been used for plug-and-play (PnP) priors to solve inverse problems in computa

FOCAL: Fine-Grained Optimal-Transport-Driven Contrastive Alignment of Language and ECGs with Waveform Enhancement

arXiv:2505.11939v3 Announce Type: replace-cross Abstract: Electrocardiograms (ECGs) are essential non-invasive tools for diagnosing cardiovascular diseases. While recent multimodal ECG-Report contrast

local-aiarxiv-cs-ai

Foundations of Stochastic Lexical Calculus: Semantic Descent and Random Dynamics on Probability Simplices

arXiv:2609.20207v1 Announce Type: new Abstract: Large language models produce prompt-dependent probabilities over words, whereas scientific systems require uncertainty over meaningful states that can

researcharxiv-cs-cl

Applications

From Models to Systems: A Comprehensive Survey of Efficient Multimodal Learning

arXiv:2609.19445v1 Announce Type: cross Abstract: The rapid expansion of multimodal models has surfaced formidable bottlenecks in computation, memory, and deployment, catalyzing the rise of Efficient

applicationsarxiv-cs-ai

FunArt: Decoding Functional Structure and Articulation from Generative 3D Latents

arXiv:2609.20673v1 Announce Type: new Abstract: To operate effectively in human environments, robots must identify articulated objects, segment their movable and interactive parts, and estimate their

G^2RA-NET: Graph-based Cross-Slice Relation Modeling with Attention Gating for Medical Image Segmentation

arXiv:2609.20088v1 Announce Type: new Abstract: Medical image segmentation supports quantitative clinical analysis and computer-aided diagnosis. Recent methods for medical image segmentation have impr

local-aiarxiv-cs-cv

GAVEL: Graph World Models for Verified and Efficient Long-Horizon LLM Task Planning

arXiv:2609.19315v1 Announce Type: cross Abstract: Large language models (LLMs) provide a flexible interface for long-horizon robot planning, but generated plans often fail to respect embodiment constr

researcharxiv-cs-ai

Generating Heterogeneous 3D Geological Microstructures from 2D Images via a Stable Diffusion-Adversarial Model

arXiv:2609.20358v1 Announce Type: new Abstract: Characterizing the physical properties of clay and cementitious materials matters across many fields, from materials science to geological waste disposa

researcharxiv-cs-ai

Applications

Generative Query Suggestion via Intent Coverage and Query-Level Credit Assignment

arXiv:2609.19209v1 Announce Type: new Abstract: Generative query suggestion aims to enhance user engagement by anticipating user intents and recommending relevant follow-up queries. A central challeng

applicationsarxiv-cs-lg

Geometrically-Constrained Radar-Inertial Odometry via Continuous Point-Pose Uncertainty Modeling

arXiv:2604.02745v2 Announce Type: replace Abstract: Radar odometry is crucial for robust localization in challenging environments; however, the sparsity of reliable returns and distinctive noise chara

local-aiarxiv-cs-ro

GLAMDRING: Gait Learning And Morphology co-Design via Reinforcement LearnING of CPGs

arXiv:2609.19452v1 Announce Type: cross Abstract: Robots are moving out of the structured factory floor and into unstructured environments such as disaster sites, planetary surfaces, and agricultural

safetyarxiv-cs-lg

Governance-as-Code: Translating EU AI Act Technical Requirements into Executable Compliance Pipelines for Generative AI Systems

arXiv:2609.20016v1 Announce Type: cross Abstract: The EU AI Act (Regulation 2024/1689) imposes technical obligations on high-risk AI providers, yet Articles 8-15 were drafted for predictive AI and lea

Graph-Based Design of Soft Grippers with Multi-Objective Quality-Diversity Optimisation

arXiv:2609.20087v1 Announce Type: new Abstract: Effective manipulation across diverse objects is critical for applications ranging from agricultural harvesting to laboratory and domestic automation. W

researcharxiv-cs-ro

GRF-Recon: Global Ray-Field Optimization for Long-Sequence Feed-forward Reconstruction

arXiv:2609.20012v1 Announce Type: new Abstract: Feed-forward 3D reconstruction provides an efficient paradigm for scene modeling from image sequences. Scaling these models to large monocular scenarios

local-aiarxiv-cs-cv

GS-PI: An Optimization-Decoupled Appearance Decomposition Approach for Generating PBR Gaussian Assets

arXiv:2609.19907v1 Announce Type: new Abstract: Gaussian Splatting (GS) excels at novel-view synthesis but encodes baked-in radiance, tightly entangling illumination with geometry and preventing seaml

Guideline-grounded retrieval-augmented generation for ophthalmic clinical decision support

arXiv:2603.21925v2 Announce Type: replace Abstract: In this work, we propose Oph-Guid-RAG, a multimodal visual RAG system for ophthalmology clinical question answering and decision support. We treat e

HerHealthEval: Evaluating Multilingual and Register-Sensitive Understanding of Women's Health Communication

arXiv:2609.20684v1 Announce Type: new Abstract: Large language models are increasingly used in healthcare communication, yet most evaluations emphasize response quality while assuming that the user's

safetyarxiv-cs-cl

Agents

HEROIC: Heterogeneous Evidential Reasoning for Open-Vocabulary Identification and Cross-Robot Collaboration

arXiv:2609.19803v1 Announce Type: new Abstract: Multi-agent heterogeneous air-ground robot teams are attractive for open world search, with applications for reconnaissance, urban search and rescue mis

agentsarxiv-cs-ro

HIL-UMI: Bringing Human-in-the-Loop Post-Training of Vision-Language-Action Models to Universal Manipulation Interface

arXiv:2609.20659v1 Announce Type: cross Abstract: Large-scale vision-language-action (VLA) models provide powerful priors for robot manipulation, yet adapting them to a specific deployment remains cha

HyperAMS-Net: Adaptive Multi-Scale Spatial Hypergraph Network for Brain Disorder Classification

model-releasesarxiv-cs-cv

arXiv:2609.19755v1 Announce Type: cross Abstract: Accurate classification of brain disorders from neuroimaging data remains challenging because of substantial inter-subject heterogeneity and the compl

Imagine-TAMP: Imagination-Guided Task and Motion Planning in Partial Observability

arXiv:2609.20396v1 Announce Type: new Abstract: Robots operating in cluttered environments must often manipulate objects whose locations are only partially observable. A central challenge is deciding

researcharxiv-cs-ro

Ischemic Stroke Segmentation and Net Water Uptake Quantification on Multicenter Non-Contrast CT Using Supervised Target-Domain Adaptation

arXiv:2609.20151v1 Announce Type: new Abstract: Objectives: Quantitative assessment of infarct hypodensity on non-contrast computed tomography (NCCT), including net water uptake (NWU), requires manual

Tutorials

JEPA-Anything: Learning Predictive Models across Different Worlds

arXiv:2609.20800v1 Announce Type: new Abstract: World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-spe

tutorialsarxiv-cs-cl

LapaTrack-3D: 6 DoF pre-operative shape tracking for laparoscopic surgery

arXiv:2609.19954v1 Announce Type: cross Abstract: This work proposes a real-time 6 Degree-of-Freedom (6 DoF) tracking algorithm for monocular laparoscopic surgery. It provides alignment between intra-

safetyarxiv-cs-cv

Tutorials

Learn Your Own Thoughts: Abstract Token Curriculum

arXiv:2609.19717v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable reasoning capabilities by utilizing chain-of-thought (CoT) as a scratchpad for intermediate stag

tutorialsarxiv-cs-ai

Learning-Based Reconstruction of Optical Properties in Bilayered Media from Single-distance Time-Resolved Reflectance Measurements

model-releasesarxiv-cs-lg

arXiv:2609.19786v1 Announce Type: new Abstract: The inverse problem of reconstructing optical properties, specifically absorption and scattering coefficients, in layered biological media from time-dom

Lens: Bringing the Right Semantic Perspective into Focus for Training-Free Multimodal Representation Learning

arXiv:2609.20252v1 Announce Type: cross Abstract: High-quality representations are essential for a wide range of downstream tasks. Dedicated embedding models are explicitly optimized for representatio

Less Is More: Graph-free Multimodal RAG via Multi-signal Late Fusion

model-releasesarxiv-cs-cl

arXiv:2609.19417v1 Announce Type: new Abstract: Graph-based retrieval-augmented generation (RAG) is widely used for multimodal, cross-document question answering. However, building corpus-level graphs

LIFD: Anchored Diffusion for 3D-Aware Scene Memory in Robotic Manipulation

arXiv:2609.19796v1 Announce Type: new Abstract: Robotic manipulation under partial observability requires spatial information that extends beyond the current view. Geometry-aware RGB features describe

safetyarxiv-cs-ro

Local Sparsity Enables Unsupervised LLM Safety Detection

arXiv:2609.20129v1 Announce Type: cross Abstract: Deployment-time safety methods for large language models (LLMs) are predominantly supervised and assume access to unsafe training data. Nevertheless,

local-aiarxiv-cs-ai

MAGS: Multi-agent Auto-formalization Guarantees Safety for Agentic Outputs

arXiv:2609.19391v1 Announce Type: new Abstract: LLM coding agents now generate complex programs at a scale that makes thorough human review increasingly difficult, raising the risk of safety and secur

MATCH: Model-Aware Tool Learning with Curriculum Scheduling and Hierarchically Gated Rewards

arXiv:2609.20082v1 Announce Type: cross Abstract: Tool learning enables large language models (LLMs) to use external tools for tasks beyond parametric knowledge. Reinforcement learning can optimize to

Applications

MetaRTL: Meta-path Attention Enhanced Relational Table Learning

arXiv:2609.19832v1 Announce Type: new Abstract: Relational table learning has gained increasing attention with the widespread use of relational databases. Existing methods typically rely on deep GNN o

applicationsarxiv-cs-ai

Agents

Mitigating Retaliatory Algorithmic Collusion in Repeated Games

arXiv:2609.20548v1 Announce Type: cross Abstract: Reinforcement learning agents trained to maximize their own reward in repeated interactions can converge to supra-competitive outcomes resembling expl

agentsarxiv-cs-ai

Hardware

Modality Discrepancy Transformer for Ambivalence and Hesitancy Recognition

arXiv:2609.19148v1 Announce Type: new Abstract: Ambivalence and hesitancy (A/H) are affective states in which individuals express contradictory signals across facial, vocal, and linguistic channels. A

hardwarearxiv-cs-cl

Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning

arXiv:2609.20389v1 Announce Type: cross Abstract: Offline policy evaluation (OPE) is crucial in high-stakes reinforcement learning applications, where new policies must be assessed reliably before dep

safetyarxiv-cs-lg

Model Specific Task Similarity for Vision Language Model Selection via Layer Conductance

arXiv:2602.01346v2 Announce Type: replace Abstract: While open sourced Vision-Language Models (VLMs) have proliferated, selecting the optimal pretrained model for a specific downstream task remains ch

Agents

Modelling and Model-Checking a ROS2 Multi-Robot System using Timed Rebeca

arXiv:2511.15227v2 Announce Type: replace Abstract: Model-based development accelerates prototyping, enables earlier experimentation, and ensures rigorous validation of system design intents. In multi

agentsarxiv-cs-ro