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MINT: Tensor Decomposition on Stacked Recurrence Matrices for Time Series Data Mining

arXiv:2608.04157v1 Announce Type: new Abstract: Recurrence plots are a time series data mining primitive applied to a variety of domains (e.g. star light curves, sound waveforms, CCT telemetry). This

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MME: Mixture of Mesh Experts with Random Walk Transformer Gating

DGX agent

arXiv:2603.00828v2 Announce Type: replace Abstract: In recent years, various methods have been proposed for mesh analysis, each offering distinct advantages and often excelling on different object cla

researcharxiv-cs-cv

6 Aug 2026

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs

arXiv:2608.04680v1 Announce Type: cross Abstract: To adopt the Vision Transformers (ViTs) in resource-constrained environment, token pruning is widely used to reduce computational cost without impacti

Multi-View Face and Gesture Animation with Dynamic Gaussians

arXiv:2608.04722v1 Announce Type: new Abstract: Creating photorealistic 3D human avatars with realistic upper-body motion remains challenging. Existing approaches either focus on the head and overlook

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Flow-matching

arXiv:2608.05103v1 Announce Type: new Abstract: Data assimilation (DA) uses Bayesian inference to update the state of a numerical forecast model with observed data. In this study, we propose a fundame

MVTOP: Multi-View Transformer-based Object Pose-Estimation

arXiv:2508.03243v2 Announce Type: replace Abstract: We present MVTOP, a novel transformer-based method for multi-view rigid object pose estimation. Through an early fusion of the view-specific feature

Neighborhood-Aware Dual Biomedical Entity Linking

arXiv:2608.04144v1 Announce Type: cross Abstract: Biomedical entity linking grounds mentions in clinical and scientific text to entities in a curated knowledge base (KB) with ontological structure, wh

NeuroPB: Scaling Neural Decoding with Pretrained Behavioral Representations

arXiv:2608.04389v1 Announce Type: new Abstract: Decoding continuous motor trajectories from neural activity is essential for developing practical brain-computer interfaces (BCIs). However, current neu

Nonparametric Goodness-of-fit Testing under Covariate Shift

arXiv:2608.04860v1 Announce Type: cross Abstract: This paper develops procedures for nonparametric goodness-of-fit testing under covariate shift, where labelled data are drawn from a source population

On Hamming-Lipschitz Type Stability of the Subdominant (Minmax) Ultrametric: Theory and Simple Proofs

arXiv:2608.04014v1 Announce Type: cross Abstract: The subdominant (minmax) ultrametric is a canonical tree-structured summary of a dissimilarity matrix, arising equivalently as the ultrametric induced

On MUON optimization: From non-convergence to an error analysis with Polar Express and the Newton-Schulz polynomial from implementations

arXiv:2608.04607v1 Announce Type: cross Abstract: Stochastic gradient descent (SGD) optimization methods are the standard instruments for the training of deep neural networks (DNNs). In many relevant

On The Suitability of Differential Dataflow For Datalog Interpretation In Highly Dynamic Settings

arXiv:2308.04214v2 Announce Type: replace-cross Abstract: In the domain of knowledge representation and reasoning within AI, datalog engines play an ever-increasingly crucial role. The crux of their o

Optimal Training-Time Scaling in Gradual Adaptation

arXiv:2608.04927v1 Announce Type: new Abstract: In gradual adaptation, how should the training time on each task change as the number of intermediate tasks increases? We study this question for overpa

Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles

arXiv:2607.17607v2 Announce Type: replace Abstract: We study whether stochastic nonconvex optimization can be reduced to ordinary static regret minimization in online convex optimization in a black-bo

ORACLE: A Multi-Objective Reinforcement Learning-Based Analog Circuit Design Optimizer with Large Language Models-Guided Exploration

arXiv:2608.04999v1 Announce Type: cross Abstract: Analog circuit design automation using reinforcement learning (RL) has emerged as a promising approach for reducing manual effort. However, many exist

Predicting Brain Morphometry with MT-GNN: Mesh Evolution in Continuous Time with Graph-Based Metric Tensor Embeddings

arXiv:2608.05132v1 Announce Type: new Abstract: Predicting how a subcortical structure's shape will evolve from a few prior scans could support prognosis and clinical-trial enrichment. Existing longit

Preverbal Uninflected and Underived Roots in Mapudungun. Wuno and Its Implications

arXiv:2608.04869v1 Announce Type: new Abstract: This study examines the grammatical status of preverbal uninflected and underived roots in Mapudungun, with particular focus on wuno 'return/re-'. Throu

PriDyG: Privacy-preserving Dynamic Graph Inference with LLM-GNN Collaboration

arXiv:2608.04255v1 Announce Type: cross Abstract: Graph inference over relational data can expose sensitive edge information, and this risk becomes more severe in dynamic graphs, where repeated model

Prototype-based Self-Supervised Multimodal Learning for PPG and Accelerometry Signals

arXiv:2510.09764v2 Announce Type: replace Abstract: Modeling multi-modal time-series data is critical for capturing system-level dynamics, particularly in biosignals where modalities such as ECG, PPG,

PSI3D: Plug-and-Play 3D Stochastic Inference with Slice-wise Latent Diffusion Prior

arXiv:2512.18367v2 Announce Type: replace-cross Abstract: Diffusion models are highly expressive image priors for Bayesian inverse problems. However, most diffusion models cannot operate on large-scal

PURPOSE: Poisoning Conflict Resolution in RAG via Proxy-Fact-Grounded Updates

arXiv:2608.04756v1 Announce Type: cross Abstract: In Retrieval-Augmented Generation (RAG), post-retrieval conflict resolution arbitrates among noisy or contradictory retrieved passages. However, the r

RAG-Stack: Co-Optimizing RAG Serving Performance and Quality

arXiv:2608.03487v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG), which augments large language model (LLM) generation with information retrieved from databases, has become a wid

Random features for Grassmannian kernel approximation with bounded rank-one projections

arXiv:2608.04227v1 Announce Type: new Abstract: We propose a family of random feature maps for scalable kernel machines on low-dimensional subspaces, ie on the Grassmannian manifold. Such representati

Reachability in 3-VAS

arXiv:2608.04786v1 Announce Type: new Abstract: We settle the exact complexity of the reachability problem in (stateless) vector addition systems (VAS) in fixed low dimension. In dimensions 2-4 it has

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training

arXiv:2608.05148v1 Announce Type: new Abstract: Procedural generators produce useful verifiable reasoning problems at scale, but have received less attention as data for completion-supervised fine-tun

Reconstructing Persistent Worlds from Narratives for Narrative-Grounded Interactive Experiences

arXiv:2608.04037v1 Announce Type: cross Abstract: Designing narrative-grounded interactive experiences remains labor-intensive because interactive content must align with the underlying world implied

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs

arXiv:2608.04048v1 Announce Type: cross Abstract: Serving large language models (LLMs) under diverse deployment constraints requires flexible trade-offs between accuracy, memory footprint, and through

RegisterBridgeMM: A Register-Centric Framework for RGB-Infrared Object Detection

arXiv:2608.04833v1 Announce Type: new Abstract: RGB-infrared (RGB-IR) object detection benefits from complementary visible and thermal cues, but effective fusion remains challenging under illumination

Regularization can make diffusion models more efficient

arXiv:2502.09151v3 Announce Type: replace Abstract: Diffusion models are one of the key architectures of generative AI. Their main drawback, however, is the computational costs. This study indicates t

Reinforcement Learning and Consumption-Savings Behavior

arXiv:2510.20748v2 Announce Type: replace-cross Abstract: This paper demonstrates how reinforcement learning can explain two puzzling empirical patterns in household consumption behavior during econom

Relational Response Fields: A General Theory of Black-Box LLM Response Consistency and Recovery

arXiv:2608.04552v1 Announce Type: new Abstract: Black-box language-model reliability is commonly pursued by sampling, prompting, voting, verifying, or iteratively revising individual answers. We ask a

Representing Visual Evidence for Item Difficulty Prediction: Visual Textualization and Image-Native Modeling

arXiv:2608.04554v1 Announce Type: new Abstract: Predicting item difficulty from content can provide an initial estimate for newly developed questions before sufficient student responses are available.

Rethinking Pixel Mean Flows via Interval Denoiser

arXiv:2608.04818v1 Announce Type: new Abstract: Modern diffusion and flow-based models are increasingly moving toward few-step, latent-free generation to bypass the computational overhead of multi-ste

Revealed Rationality: Label-Free Evaluation and Regularization from Representation Theorems

arXiv:2608.05015v1 Announce Type: cross Abstract: Representation theorems in decision theory establish that behavior satisfies certain axioms if and only if it can be rationalized by a well-defined ob

Review Text as a Leading Indicator of Displayed Reputation in Platform Rating Systems: Evidence from 34 U.S. Short-Term Rental Markets

arXiv:2504.14053v2 Announce Type: replace-cross Abstract: Rating systems on accommodation platforms suffer from a familiar problem: nearly every listing displays a nearly perfect score, so the number

REZE: Recognition-Based Zero-Shot Extraction for Video Temporal Grounding

arXiv:2608.04480v1 Announce Type: new Abstract: Video temporal grounding (VTG) refers to the task of identifying the time interval in a video that corresponds to a given natural-language query. A comm

RiboSphere: Learning Unified and Efficient Representations of RNA Structures

arXiv:2603.19636v2 Announce Type: replace Abstract: Accurate RNA structure modeling remains difficult because RNA backbones are highly flexible, non-canonical interactions are prevalent, and experimen

Right Reset: Chunking by Prefix Removal

arXiv:2608.04330v1 Announce Type: new Abstract: Removing the left context from a causal language model reveals a useful kind of boundary: an edge where the model processes the same right-hand tokens w

RingSQL: Schema-Independent Synthetic Data Generation for Text-to-SQL Reinforcement Learning

arXiv:2601.05451v2 Announce Type: replace-cross Abstract: Recent advances in text-to-SQL have been driven by larger models, better datasets, and new training methods like RLVR. However, progress remai

RUTA: Principled Visual Token Allocation via Rate-Utility Optimization

arXiv:2608.04132v1 Announce Type: new Abstract: High-resolution images and long videos provide vision-language models with rich context for multimodal reasoning and fine-grained perception, but the re

Sample Complexity of Multicalibration for Multilevel Properties

arXiv:2608.04288v1 Announce Type: new Abstract: Calibration requires a predictor to be unbiased after conditioning on its own predictions. Multicalibration asks for this guarantee simultaneously acros

Searching for Sound-Meaning Collisions: Graph-Based Affordance Retrieval and Multi-Evaluator Ranking for Pun Translation at CLEF 2026 JOKER Task 2

arXiv:2608.04299v1 Announce Type: new Abstract: Fifteen years ago, Low proposed that pun translators should stop searching for equivalent words and instead search for new points of contact between sou

Season: Spectrum-Aware Orthogonal Gradient Refinement for Transfer-Based Adversarial Attacks

arXiv:2608.04441v1 Announce Type: new Abstract: Transfer-based adversarial attacks often transfer poorly across heterogeneous architectures because CNNs favor local textures while Vision Transformers

Seeking Physics in Diffusion Noise

arXiv:2603.14294v3 Announce Type: replace-cross Abstract: Do video diffusion models encode signals predictive of physical plausibility? We probe intermediate denoising representations of pretrained Di

Segmentation Pre-training for Label-Efficient Lumbar Spine Degeneration Grading

arXiv:2608.04810v1 Announce Type: new Abstract: Automated assessment of degenerative pathology in the lumbar spine on magnetic resonance imaging (MRI) requires access to large-scale datasets of expert

SHIELD: A Segmented Hierarchical Memory Architecture for Energy-Efficient LLM Inference on Edge NPUs

arXiv:2604.07396v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) inference on edge Neural Processing Units (NPUs) is fundamentally constrained by limited on-chip memory capacity. A

SiMDex: Mining Similar Egocentric Videos for Cross-Embodiment Dexterous Manipulation

arXiv:2608.04196v1 Announce Type: cross Abstract: Recent years have witnessed an explosive trend of scaling ego-centric human videos for robot manipulation, yet it remains unclear which data actually

Simile Understanding in Text-to-Image Models: An Evaluation Framework

arXiv:2608.04750v1 Announce Type: cross Abstract: Similes provide a compact and expressive way to describe visual characteristics in text prompts. Recent text-to-image models (t2i models) can produce