Search: “models”

HyperSpace: A Generalized Framework for Spatial Encoding in Hyperdimensional Representations

arXiv:2604.15113v2 Announce Type: replace Abstract: Vector Symbolic Architectures (VSAs) provide a well-defined algebraic framework for compositional representations in hyperdimensional spaces. We int

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Tutorials

Improving Generative Adversarial Networks with Self-Distillation

DGX agent

arXiv:2605.08577v1 Announce Type: new Abstract: In modern GANs, maintaining an Exponential Moving Average (EMA) of the generator's weights is a standard practice, as such an averaged model consistentl

tutorialsarxiv-cs-cv

12 May 2026

Improving Lexical Difficulty Prediction with Context-Aligned Contrastive Learning and Ridge Ensembling

arXiv:2605.08950v1 Announce Type: cross Abstract: Lexical difficulty prediction is a fundamental problem in language learning and readability assessment, requiring models to estimate word difficulty a

Improving TMS EEG Signal Quality for Closed-Loop Neuro Stimulation via Source-Domain Denoising

arXiv:2605.08184v1 Announce Type: cross Abstract: This research addresses a validated TMS EEG cleaning pipeline and a corresponding benchmark dataset. It evaluates two widely used artifact removal pip

Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions

arXiv:2605.09870v1 Announce Type: cross Abstract: We propose SVAR-FM (Structural VAR with Flow Matching), a framework for time series causal discovery that treats a physics-based simulator as a mechan

Inverse Design of Multi-Layer Sub-Pixel-Resolution RF Passives Through Grayscale Diffusion with Flexible S-Parameter Conditioning

arXiv:2605.08233v1 Announce Type: cross Abstract: Inverse design of RF passive components from S-parameters is a high-dimensional, ill-posed problem, and prior generative approaches are limited to sin

Local Ai

iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning

arXiv:2605.10732v1 Announce Type: cross Abstract: Automated transit payment analysis is vital for scalable fare auditing and passenger analytics, yet practice still relies on limited manual inspection

local-aiarxiv-cs-ai

Kinetic theory for Transformers and the lost-in-the-middle phenomenon

arXiv:2605.09213v1 Announce Type: cross Abstract: We study causal self-attention dynamics -- a toy model for decoder Transformers -- which we interpret as a non-exchangeable interacting particle syste

KV-RM: Regularizing KV-Cache Movement for Static-Graph LLM Serving

arXiv:2605.09735v1 Announce Type: cross Abstract: Static-graph LLM decoders provide predictable launches, fixed tensor shapes, and low submission overhead, but online decoding exposes highly irregular

Language Conditioned Multi-Finger Dexterous Manipulation Enabled by Physical Compliance and Switching of Controllers

arXiv:2410.14022v2 Announce Type: replace-cross Abstract: Human dexterity arises from combining high-level task reasoning with finger-level dexterity control and physical compliance at the muscle and

Latent Personality Alignment: Improving Harmlessness Without Mentioning Harms

arXiv:2605.08496v1 Announce Type: new Abstract: Current adversarial robustness methods for large language models require extensive datasets of harmful prompts (thousands to hundreds of thousands of ex

Applications

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling

arXiv:2605.10292v1 Announce Type: cross Abstract: Time series forecasting serves as an essential tool for many real-world applications, supporting tasks such as resource optimization and decision-maki

applicationsarxiv-cs-ai

Learning Confidence Ellipsoids and Applications to Robust Subspace Recovery

arXiv:2512.16875v4 Announce Type: replace-cross Abstract: We study the problem of finding confidence ellipsoids for an arbitrary distribution in high dimensions. Given samples from a distribution D an

Learning to Align Generative Appearance Priors for Fine-grained Image Retrieval

arXiv:2605.09859v1 Announce Type: new Abstract: Fine-grained image retrieval (FGIR) typically relies on supervision from seen categories to learn discriminative embeddings for retrieving unseen catego

safetyarxiv-cs-cv

Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization

arXiv:2605.08978v1 Announce Type: new Abstract: Recent advancements in agentic test-time scaling allow models to gather environmental feedback before committing to final actions. A key limitation of e

Tutorials

Learning to Learn the Macroscopic Fundamental Diagram using Physics-Informed and meta Machine Learning techniques

arXiv:2508.14137v2 Announce Type: replace Abstract: The Macroscopic Fundamental Diagram is a popular tool used to describe traffic dynamics in an aggregated way, with applications ranging from traffic

tutorialsarxiv-cs-lg

Learning to Sparsify Stochastic Linear Bandits

arXiv:2605.10151v1 Announce Type: new Abstract: This paper addresses the problem of learning to sparsify stochastic linear bandits, where a decision-maker sequentially selects actions from a high-dime

Learning When to Trust LLM Priors: A Validated Framework for Semantic Prior Integration

arXiv:2601.21410v3 Announce Type: replace-cross Abstract: Large language models (LLMs) encode rich semantic knowledge that can be useful for supervised learning, but their outputs are unreliable as st

LimeCross: Context-Conditioned Layered Image Editing with Structural Consistency

model-releasesarxiv-cs-cv

arXiv:2605.10319v1 Announce Type: new Abstract: Layered image assets are widely used in real-world creative workflows, enabling non-destructive iteration and flexible re-composition. Recent advances i

Agents

MAGE: Multi-Agent Self-Evolution with Co-Evolutionary Knowledge Graphs

arXiv:2605.10064v1 Announce Type: new Abstract: Self-evolving language-model agents must decide what to learn next and how to preserve what they have learned across iterations. Existing systems typica

agentsarxiv-cs-ai

MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

model-releasesarxiv-cs-ro

arXiv:2605.10760v1 Announce Type: new Abstract: Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi

MARS-SQL: A multi-agent reinforcement learning framework for Text-to-SQL

arXiv:2511.01008v2 Announce Type: replace Abstract: Large Language Models (LLMs) often struggle with the precise logic and schema alignment required for complex Text-to-SQL tasks. While current method

safetyarxiv-cs-cl

MASS-DPO: Multi-negative Active Sample Selection for Direct Policy Optimization

arXiv:2605.10784v1 Announce Type: new Abstract: Multi-negative preference optimization under the Plackett--Luce (PL) model extends Direct Preference Optimization (DPO) by leveraging comparative signal

safetyarxiv-cs-lg

MC^2: Monte Carlo Correction for Fast Elliptic PDE Solving

arXiv:2605.09288v1 Announce Type: cross Abstract: Partial differential equation (PDE) solvers underpin scientific computing, but real-world deployment is bounded by compute. Classical Monte Carlo solv

MDGYM: Benchmarking AI Agents on Molecular Simulations

arXiv:2605.08941v1 Announce Type: new Abstract: The promise of AI-driven scientific discovery hinges on whether AI agents can autonomously design and execute the computational workflows that underpin

MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems

model-releasesarxiv-cs-ro

arXiv:2605.10904v1 Announce Type: new Abstract: Vehicle-to-Everything (V2X) communication has emerged as a promising paradigm for autonomous driving, enabling connected agents to share complementary p

MedFL-Stress: A Systematic Robustness Evaluation of Federated Brain Tumor Segmentation under Cross-Hospital MRI Appearance Shift

arXiv:2605.09025v1 Announce Type: new Abstract: Federated learning enables hospitals to collaboratively train segmentation models without sharing patient data. However, current evaluation protocols re

safetyarxiv-cs-cv

Tutorials

MEG-XL: Data-Efficient Brain-to-Text via Long-Context Pre-Training

arXiv:2602.02494v2 Announce Type: replace Abstract: Clinical brain-to-text interfaces are designed for paralysed patients who cannot provide extensive training recordings. Pre-training improves data-e

tutorialsarxiv-cs-lg

Mela: Test-Time Memory Consolidation based on Transformation Hypothesis

arXiv:2605.10537v1 Announce Type: new Abstract: Memory consolidation, the process by which transient experiences are transformed into stable, structured representations, is a foundational organizing p

researcharxiv-cs-cl

Memory Inception: Latent-Space KV Cache Manipulation for Steering LLMs

arXiv:2605.06225v2 Announce Type: replace-cross Abstract: Steering large language models (LLMs) is usually done by either instruction prompting or activation steering. Prompting often gives strong con

MemQ: Integrating Q-Learning into Self-Evolving Memory Agents over Provenance DAGs

arXiv:2605.08374v1 Announce Type: new Abstract: Episodic memory allows LLM agents to accumulate and retrieve experience, but current methods treat each memory independently, i.e., evaluating retrieval

Micro-Defects Expose Macro-Fakes: Detecting AI-Generated Images via Local Distributional Shifts

arXiv:2605.09296v1 Announce Type: cross Abstract: Recent generative models can produce images that appear highly realistic, raising challenges in distinguishing real and AI-generated images. Yet exist

researcharxiv-cs-ai

Mitigating Many-shot Jailbreak Attacks with One Single Demonstration

arXiv:2605.08277v1 Announce Type: cross Abstract: Many-shot jailbreaking (MSJ) causes safety-aligned language models to answer harmful queries by preceding them with many harmful question-answer demon

Mitigating Membership Inference in Intermediate Representations with Differentially Private Training

arXiv:2602.22611v2 Announce Type: replace Abstract: In Embedding-as-an-Interface (EaaI) settings, pre-trained models are queried for Intermediate Representations (IRs). The distributional properties o

MonitoringBench: Semi-Automated Red-Teaming for Agent Monitoring

arXiv:2605.09684v1 Announce Type: cross Abstract: We introduce a red-teaming methodology that exposes harder-to-catch attacks for coding-agent monitors, suggesting that current practices may under-eli

MPerS: Dynamic MLLM MixExperts Perception-Guided Remote Sensing Scene Segmentation

arXiv:2605.10769v1 Announce Type: cross Abstract: The multimodal fusion of images and scene captions has been extensively explored and applied in various fields. However, when dealing with complex rem

Multi-Level Graph Attention Network Contrastive Learning for Knowledge-Aware Recommendation

arXiv:2605.08499v1 Announce Type: cross Abstract: In recent years, the use of edge information provided by knowledge graphs together with the advantages of higher-order connectivity in graph neural ne

researcharxiv-cs-ai

MultiMedVision: Multi-Modal Medical Vision Framework

arXiv:2605.09151v1 Announce Type: new Abstract: Multi-modal medical imaging enables comprehensive diagnostics, yet current foundation models process 2D (e.g. X-ray) and 3D (e.g. CT) data with separate

researcharxiv-cs-cv

NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation

arXiv:2605.10813v1 Announce Type: new Abstract: LLM-powered multi-agent systems can now automate the full research pipeline from ideation to paper writing, but a fundamental question remains: automati

Neural Cluster First, Route Second: One-Shot Capacitated Vehicle Routing via Differentiable Optimal Transport

arXiv:2605.09301v1 Announce Type: cross Abstract: The Capacitated Vehicle Routing Problem (CVRP) underpins modern last-mile logistics. Current Neural Combinatorial Optimization (NCO) methods construct

Neural Information Causality

arXiv:2605.09316v1 Announce Type: cross Abstract: Query-separated computation forces a representation to play an operational role: data are encoded before a query is known, and a later decoder can ans

Neural Weight Norm = Kolmogorov Complexity

arXiv:2605.10878v1 Announce Type: new Abstract: Why does weight decay work? We prove that, in any fixed-precision regime, the smallest weight norm of a looped neural network outputting a binary string

Local Ai

New AI-Driven Tools for Enhancing Campus Well-being: A Prevention and Intervention Approach

arXiv:2605.10804v1 Announce Type: new Abstract: Campus well-being underpins academic success, yet many universities lack effective methods for monitoring satisfaction and detecting mental health risks

local-aiarxiv-cs-ai

Applications

Noise-Started One-Step Real-World Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement

arXiv:2605.09328v1 Announce Type: new Abstract: Pre-trained text-to-image (T2I) diffusion models have shown strong potential for real-world image super-resolution (Real-ISR), owing to their noise-star

applicationsarxiv-cs-cv

Normalization Equivariance for Arbitrary Backbones, with Application to Image Denoising

arXiv:2605.08193v1 Announce Type: cross Abstract: Normalization Equivariance (NE), equivariance to global contrast and brightness transforms, improves robustness to distribution shift in image-to-imag

On the Convergence Rate of LoRA Gradient Descent

arXiv:2512.18248v3 Announce Type: replace Abstract: The low-rank adaptation (LoRA) algorithm for fine-tuning large models has grown popular in recent years due to its remarkable performance and low co

Tutorials

One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification

arXiv:2605.10179v1 Announce Type: cross Abstract: Neural Flows efficiently model irregular multivariate time series by directly learning ODE solution trajectories with neural networks, bypassing step-

tutorialsarxiv-cs-ai

One-step Latent-free Image Generation with Pixel Mean Flows

arXiv:2601.22158v3 Announce Type: replace Abstract: Modern diffusion/flow-based models for image generation typically exhibit two core characteristics: (i) using multi-step sampling, and (ii) operatin

researcharxiv-cs-cv