Search: “framework”

FreqFLD: Towards All-in-One Facial Landmark Detection via Frequency Modulation

arXiv:2609.10278v1 Announce Type: new Abstract: Recent progress in deep learning has significantly advanced facial landmark detection. However, most existing methods process features in a spatial-doma

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Research

Frequency-Conditioned Flow Matching for Vision-Language-Action Models

DGX agent

arXiv:2609.10405v1 Announce Type: new Abstract: Robot actions are temporally correlated trajectories whose frequency components encode motion at different scales with highly non-uniform energy distrib

researcharxiv-cs-ro

10 Sept 2026

From Few-Shot Segmentation to Clinician-in-the-Loop Medical Image Analysis

arXiv:2609.10001v1 Announce Type: new Abstract: Few-shot medical image segmentation (FSMIS) seeks to delineate unseen structures from a small support set, but its standard formulation fixes task-defin

From Pixels to Hierarchical Sequences: Quadtree Mask Encoding for Vision-Language Binary Change Detection

arXiv:2609.09876v1 Announce Type: new Abstract: Dense change detection in remote sensing requires vision-language models (VLMs) to compare bi-temporal images and generate accurate pixel-level masks. E

Hardware

From Splats to Silicon: Rethinking Computational Efficiency of 3DGS

arXiv:2609.06157v1 Announce Type: cross Abstract: 3D Gaussian splatting (3DGS) represents scenes with explicit primitives and supports real-time novel-view synthesis, yet its system efficiency varies

hardwarearxiv-cs-ai

Future-Aware Flow Planning for Safe UAV Target Following

arXiv:2609.10166v1 Announce Type: new Abstract: UAV target following in cluttered environments is inherently predictive: current-state followers can lag behind turns, choose blocked corridors, or trad

safetyarxiv-cs-ro

Geometric organization of olfactory descriptor data in the Poincare disk

arXiv:2609.09573v1 Announce Type: cross Abstract: Odor quality is commonly represented using high dimensional descriptor profiles, yet their low dimensional organization remains unclear. We investigat

GoAnt: Quality-Diversity Multi-Agent Search for Alpha Factor Discovery in Market Microstructure Data

arXiv:2609.08719v1 Announce Type: new Abstract: Automated alpha factor discovery searches symbolic trading signals from price-volume panels and order-book data under a fixed evaluation budget. Existin

Graph-Based Personalized Memory for LLM Agents: Representation, Evolution, Retrieval, and Evaluation

arXiv:2609.08599v1 Announce Type: new Abstract: Large Language Model (LLM) agents are evolving from single-session tools toward long-term personal assistants that must adapt to individual users across

Tutorials

Guiding Image-to-3D Generation with Test-Time Partial Observations

arXiv:2609.10531v1 Announce Type: new Abstract: Image-to-3D models can generate visually compelling 3D assets from a single RGB image, but their geometry is often only loosely constrained by the avail

tutorialsarxiv-cs-cv

High-probability guarantees for linear accessibility in feature superposition

arXiv:2609.09556v1 Announce Type: cross Abstract: Neural networks can leverage feature superposition to encode more concepts than dimensions, but cross-feature interference constrains the linear acces

HiRAD: A Flexible Large-Scale AGV Routing System

arXiv:2609.09752v1 Announce Type: new Abstract: Automatic Guided Vehicles (AGVs) substantially boost warehouse throughput, but routing large-scale AGV fleets remains challenging. Classical Multi-Agent

agentsarxiv-cs-ro

Human-agent discovery of reconfigurable in-plane ferroelectric superdomain control

arXiv:2609.06887v1 Announce Type: cross Abstract: Automated experimentation is most effective when the observables, available actions, and objective are defined before the experiment starts, as is the

safetyarxiv-cs-ai

HybridFLow: SDN-Orchestrated Client Partitioning for Hybrid Federated Learning

arXiv:2609.10404v1 Announce Type: cross Abstract: Cross-silo Federated Learning (FL) enables geographically distributed institutions to collaboratively train machine learning models without sharing ra

HyperTrace: Hypothesis-Based Preference Tracing for Online LLM Personalization

arXiv:2609.09835v1 Announce Type: new Abstract: Personalized language models aim to adapt responses to individual users, whose preferences are often latent and revealed gradually through interaction.

Improving Proficiency and Efficiency of Android GUI Agents via Self-Generating Tool Actions

arXiv:2609.06792v1 Announce Type: new Abstract: Android agents using a hybrid action space that combines GUI actions and tool actions (e.g., accessing application data via APIs) remain largely underex

In-Place Instruction Following in Diffusion Language Models

arXiv:2609.07160v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) generate text via bidirectional iterative denoising, naturally supporting user-specified constraints anchored

Inference-Time Graph Engineering for Multi-Agent LLM Workflows

arXiv:2609.05774v1 Announce Type: new Abstract: Recent multi-agent LLM systems increasingly rely on graph-structured communication to coordinate specialized agents. We revisit multi-agent orchestratio

Inferring the Unspoken: Aligning Embodied Agents with Implicit Preferences

arXiv:2502.00858v4 Announce Type: replace Abstract: Natural-language instructions rarely specify every detail required for embodied action. An agent asked to ``prepare an apple,'' for example, must st

Influence-Oriented Personalized Federated Learning

model-releasesarxiv-cs-lg

arXiv:2410.03315v2 Announce Type: replace Abstract: Federated learning (FL) is a machine learning paradigm where clients with different behaviors and preferences can learn collaboratively without comp

Integrated Prediction and Multi-period Portfolio Optimization

arXiv:2512.11273v3 Announce Type: replace-cross Abstract: Multi-period portfolio optimization is important for real portfolio management, as it accounts for transaction costs, path-dependent risks, an

Applications

Integrating Unimodal and Vision-Language Representations in Latent Space for Multi-Label Chest X-Ray Classification

arXiv:2609.09185v1 Announce Type: new Abstract: Multi-label chest X-ray classification has attracted considerable attention in recent years, with the effective use of visual representations and clinic

applicationsarxiv-cs-cv

JEPA Policy: Diffusion-Free Imitation Learning via Paired Action and Future Representation Prediction

arXiv:2609.09630v1 Announce Type: new Abstract: Standard behavior cloning supervises actions without explicitly constraining the future representation paired with each demonstrated action chunk. We in

safetyarxiv-cs-ro

LatentDx: Latent Multi-Agent Communication for Cross-Hospital Rare-Disease Diagnosis

arXiv:2606.13945v2 Announce Type: replace Abstract: Rare diseases affect over 300 million patients across more than 7{,}000 conditions, yet no single hospital encounters enough cases of any one condit

Learning to Adapt and Calibrate: Score Distribution Alignment for Few-Shot Uncertainty Prediction in Medical VLMs

arXiv:2609.10333v1 Announce Type: new Abstract: Uncertainty estimation for medical vision--language models (VLMs) using conformal prediction has gained increasing attention due to its distribution-fre

Leveraging Fine-grained Error Correction in Korean Speech Recognition for Consultation Services

arXiv:2609.09889v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) technology is fundamental to customer service automation and large-scale transcription. However, even advanced ASR mo

Limits of Reliability and Scaling in Language Models

arXiv:2607.14112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are trained and evaluated as though perfect reliability is achievable for any task given sufficient scale. We sho

researcharxiv-cs-ai

Literati: Towards Anytime Optimal Shape Generalized Trees via AO*

arXiv:2609.09299v1 Announce Type: new Abstract: Decision trees are prized for their interpretability and strong performance on tabular data, but popular greedy top-down induction algorithms can yield

safetyarxiv-cs-lg

LLM-Generated or Human-Written? Comparing Review and Non-Review Papers on ArXiv

arXiv:2601.17036v2 Announce Type: replace-cross Abstract: ArXiv recently prohibited the upload of unpublished review papers to its servers in the Computer Science domain, citing a high prevalence of L

safetyarxiv-cs-cl

Mapping the Emerging Social Science of Large Language Models

arXiv:2609.07598v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly shape communication, learning, work, creativity, and decision-making, yet social-science research on these d

safetyarxiv-cs-ai

Marker-free eye-gaze estimation using a single image and depth from defocus

arXiv:2609.09610v1 Announce Type: new Abstract: This paper presents a marker-free eye-gaze estimation approach using a single 2D camera, such as an integrated laptop webcam. The gaze-related features

Measuring LLM Sycophancy under Sustained Multi-Turn Pressure

arXiv:2609.09090v1 Announce Type: cross Abstract: Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations t

MeClear: Cooperative Game-Theoretic Attribution and Risk-Aware Memory Clearance for Long-Horizon LLM Agents

arXiv:2609.09115v1 Announce Type: new Abstract: Long horizon Large Language Model (LLM) agents rely on external memory systems to preserve user preferences and task knowledge across extended interacti

MedDeID enables locally governed clinical-text de-identification from real or synthetic training data

arXiv:2609.10049v1 Announce Type: new Abstract: Clinical notes contain personally identifiable information (PII), restricting reuse for research and medical AI, especially when data cannot leave an in

MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra

arXiv:2609.09436v1 Announce Type: cross Abstract: Minimum-norm confidence envelope strategies offer a nonparametric approach to constructing nonasymptotic, simultaneous confidence regions for band-lim

Multi-dimensional Preference Alignment by Conditioning Reward Itself

arXiv:2512.10237v2 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback has emerged as a standard for aligning diffusion models. However, we identify a fundamental limitation in

MVFA: A Multi-View Text-Guided Multimodal Fusion LLM Adapter for Sentiment Analysis and Emotion Recognition

arXiv:2609.06188v1 Announce Type: new Abstract: Multimodal sentiment analysis and emotion recognition in conversations demand effective modeling of heterogeneous interactions across textual, acoustic,

Myocardial Strain Drift Correction in Deep Learning Based Ultrasound Tracking

arXiv:2609.09577v1 Announce Type: cross Abstract: Myocardial strain from echocardiography is a key biomarker for cardiac function. Recent deep learning methods show strong performance for myocardial m

Neptune: An AI model for Global Ocean Subseasonal Prediction

arXiv:2609.08606v1 Announce Type: cross Abstract: Subseasonal-to-seasonal (S2S) forecasting is societally critical, supporting decision-making in sectors ranging from water and agricultural management

researcharxiv-cs-ai

Neutralizing Popularity Bias in LLM-based Recommendation via Counterfactual Reasoning Guidelines

arXiv:2503.08051v2 Announce Type: replace Abstract: In the era of generative AI, recommender systems are moving from precise prediction to trustworthy generation. Large language models (LLMs) support

NEXUS-MI: Communication-Aware Federated Personalization for Gateway-Coordinated Motor-Imagery Brain-Computer Interfaces

arXiv:2609.09786v1 Announce Type: new Abstract: Electroencephalography (EEG)-based motor-imagery brain-computer interfaces (MI-BCIs) vary across subjects and sessions, complicating personalization fro

No Free Checker: A Survey of Verifiers for Robot Policies

arXiv:2609.09250v1 Announce Type: cross Abstract: A verifier for robot policies reads a candidate behavior and returns a score for how well it did, used both to evaluate vision-language-action policie

OmniPoint: Universal Monocular Metric Pointcloud from Any Camera

arXiv:2609.09394v1 Announce Type: new Abstract: Recovering metric 3D geometry from monocular images is a fundamental computer vision task, yet current methods remain heavily fragmented by fixed camera

PocketAgents: A Manifest-Driven Library of Autonomous Defense Agents

arXiv:2605.21694v2 Announce Type: replace-cross Abstract: Connecting large language models (LLMs) to defensive enforcement requires more than asking a model whether an attack is happening. A defender

Positional task conditioning for scalable defect detection across product families in large product catalogs

arXiv:2609.09567v1 Announce Type: new Abstract: Product families in large product catalogs suffer from inconsistencies such as duplicates and unit mismatches that degrade customer experience. Detectin

ProbPlug: A Plugin Uncertainty Network for Reliable Confidence in LLM Binary Classification

arXiv:2609.10122v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance across a broad range of classification settings, yet the reliability of their predictions

researcharxiv-cs-cl

Local Ai

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents

arXiv:2609.09153v1 Announce Type: new Abstract: Large language models are increasingly deployed as agents that plan over long horizons and act through external tools. Most agents select actions throug

local-aiarxiv-cs-ai

Programmable World Model

model-releasesarxiv-cs-cv

arXiv:2609.10540v1 Announce Type: new Abstract: Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent wo