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SCORE: Spectral Correlation Estimation for Multivariate Gaussians

arXiv:2610.12096v1 Announce Type: new Abstract: Neural network-based predictive modeling with high-dimensional structured Gaussian targets requires an efficient and numerically stable, yet expressive

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Selective Listening: Mechanism-Guided Control of Audio Influence in Large Audio-Language Models

DGX agent

arXiv:2610.11196v1 Announce Type: cross Abstract: Large audio-language models (LALMs) exploit multimodal evidence, yet task-irrelevant audio can alter text-reasoning decisions when listening is unnece

researcharxiv-cs-cl

9 Oct 2026

Self-Organization from Constrained Geometric Radiation

arXiv:2610.10621v1 Announce Type: new Abstract: How does dynamic order emerge spontaneously in closed systems without external driving? Existing paradigms all require external energy flows, temperatur

Self-Supervised Speech Representations for Cross-Speaker Dysarthria Detection During Awake Craniotomy

arXiv:2610.11825v1 Announce Type: new Abstract: Detecting intra-operative speech impairment during awake craniotomy is essential for preserving language function. However, automated detection remains

SFT-as-Context Mitigates Forgetting in Supervised Fine-Tuning

arXiv:2610.11132v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) equips large language models (LLMs) with specialized capabilities, but often comes at the cost of forgetting the general

sigmaTransfer: Uncertainty Transfer from Small to Large Networks under muP

arXiv:2610.11668v1 Announce Type: cross Abstract: Reliable predictive uncertainty in Laplace approximations depends critically on the prior precision, yet selecting it requires a posterior sweep that

Similar Predictive Fit but Different Latent Dynamics: Characterizing Learned Dynamical Structure in Personalized Models of Brain Disorders

arXiv:2610.10850v1 Announce Type: new Abstract: As AI models move toward clinical decision-making and personalized treatment, understanding what a model learns is important beyond predictive accuracy

Similarity-as-Evidence: Calibrating Overconfident VLMs for Interpretable and Label-Efficient Medical Active Learning

arXiv:2602.18867v3 Announce Type: replace Abstract: Active Learning (AL) reduces annotation costs in medical imaging by selecting only the most informative samples for labeling, but suffers from cold-

Slot3R: Set-Associative Spatial Memory for Streaming 3D Reconstruction

arXiv:2610.12282v1 Announce Type: new Abstract: Streaming 3D reconstruction must preserve evidence from each frame while processing an expanding scene online. Spatial memory is a natural fit because i

SLVR: Structured Latent Visual Reasoning via Human-like Reasoning Flows

arXiv:2610.10563v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) often answer visual reasoning questions by relying on linguistic priors rather than task-relevant visual evid

Social Pain Disrupts Emotion-Action Brain-State Dynamics in Adolescents with Non-Suicidal Self-Injury

arXiv:2610.11155v1 Announce Type: new Abstract: Non-suicidal self-injury (NSSI) is prevalent among adolescents with depression, but the rapid brain-state dynamics linking social distress to maladaptiv

SP-DocReader: Difference-Aware Self-Play for Precise Document OCR

arXiv:2610.11148v1 Announce Type: cross Abstract: Accurate page transcription remains difficult for vision language models under limited input and training budgets. We present SP-DocReader, a self-pla

SpaceFlow: Locally Controllable 3D Generation

arXiv:2610.12399v1 Announce Type: cross Abstract: Current 3D generation methods lack explicit local control: geometric adherence is often defined by a global control strength, and appearance cannot be

Sparse Attention Is Matrix Approximation, Not Choosing from a Bag of Values

arXiv:2610.10871v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong performance across many domains, but their efficiency is limited by the quadratic cost of attention with res

SPD-MetaFormer is what you need for small-data brain decoding

arXiv:2610.10952v1 Announce Type: new Abstract: Brain signal decoding is challenging because neural recordings are noisy and vary across individuals, while labeled data are often limited. Recent atten

Specialized Decision Models vs. General-Purpose LLMs: Benchmarking Jev Across Knowledge, Reasoning, and Multilingual Tasks

arXiv:2610.11978v1 Announce Type: new Abstract: Jev is a 'System One' model that returns a choice among given options instead of generating text. We study how such a specialized decision model compare

Speedbumps: Rejection Attacks on Speculative Decoding

arXiv:2610.10929v1 Announce Type: cross Abstract: Speculative decoding is a popular technique for increasing the speed and reducing the costs of large language model (LLM) inference by verifying multi

SR-TTA: Spatial-Redundancy Test-Time Adaptation for Interference-Robust Respiration Sensing

arXiv:2610.11755v1 Announce Type: new Abstract: Future 6G networks aim to expose sensing as a native service by reusing communication infrastructure. We study respiration sensing on a cell-free massiv

SRUG: A Fusion-Driven Generator Network for Medical Image Translation

arXiv:2601.04785v2 Announce Type: replace-cross Abstract: MRI sequence synthesis aims to recover missing image contrast while preserving patient-specific anatomy. The choice of generation mechanism af

SteerCast: Retrieval-Based Latent Steering for Decoder-Only Time Series Forecasting

arXiv:2610.11229v1 Announce Type: new Abstract: Time series forecasting aims to predict future values from historical observations and auxiliary features. We propose extbf{SteerCast}, a retrieval-base

Streaming-Aware Diffusion for Real-Time Video Super-Resolution via Cross-Step Attention

arXiv:2610.11746v1 Announce Type: new Abstract: Real-time video super-resolution requires high spatio-temporal fidelity under strict latency constraints, challenging diffusion models due to their iter

Stride Independent Patching for Deep Learning

arXiv:2610.12216v1 Announce Type: new Abstract: This paper presents semi-automatic stride-independent patching (SSP) as an alternative to automatic stride-dependent patching techniques. SSP uses user

Structured Sentiment Analysis Using Sequence Labeling as Dependency Graph Parsing

arXiv:2610.11695v1 Announce Type: new Abstract: This study addresses the problem of structured sentiment analysis, whose goal is to obtain a fine-grained sentiment graph where the nodes represent span

Subspace Uncertainty and Sharp Sampling Thresholds on the Boolean Cube

arXiv:2610.12358v1 Announce Type: cross Abstract: We study Gaussian regression under squared population L_2 loss in a known m-dimensional subspace of degree-at-most-k functions on the d-dimensional Bo

Tabula Rasa: Monte Carlo estimation of unit-variance noise with controlled spatio-temporal correlation

arXiv:2610.11653v1 Announce Type: cross Abstract: We suggest a method to generate time-varying Gaussian noise with controlled variance and controlled temporal correlation. This noise is used in severa

TAM: Task-Aware Memory Distillation for Efficient Spatiotemporal Prediction

arXiv:2610.11617v1 Announce Type: cross Abstract: Knowledge distillation enables efficient spatiotemporal prediction by transferring knowledge from an accurate teacher to a compact student. However, m

TAP3D: Thermal-Assisted 3D Human Point Clouds

arXiv:2610.11241v1 Announce Type: new Abstract: Human body point clouds are a versatile representation for AI-enabled human sensing. However, existing methods using LiDAR, radar, and depth cameras suf

TAPNAV: Humanoid Navigation through Tactile Active Perception

arXiv:2610.10748v1 Announce Type: new Abstract: Navigation in vision-denied environments is challenging for humanoid robots because proprioceptive odometry drifts and localization uncertainty accumula

researcharxiv-cs-ro

Task-Centric Personalized Federated Fine-Tuning of Language Models

arXiv:2604.00050v3 Announce Type: replace-cross Abstract: Federated Learning (FL) has emerged as a promising technique for training language models on distributed and private datasets of diverse tasks

Temporal transformer CAN encoder with federated lightweight heads for anomaly detection

arXiv:2610.10613v1 Announce Type: new Abstract: Modern vehicles rely on large numbers of Electronic Control Units (ECUs) that constantly exchange information over the Controller Area Network (CAN) bus

Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching

arXiv:2602.22871v2 Announce Type: replace-cross Abstract: Reasoning with large language models often benefits from generating multiple chains-of-thought, but existing aggregation strategies are typica

The Ball and the Box: Two Geometries of Computation in Superposition

arXiv:2610.11744v1 Announce Type: new Abstract: Neural representations can encode more features than they have dimensions, a phenomenon known as superposition. We study the dimension needed to compute

The Kinetics Observer: A Tightly Coupled Estimator for Legged Robots

arXiv:2406.13267v2 Announce Type: replace Abstract: This paper presents the Kinetics Observer, a novel proprioceptive state estimator for legged robots designed to provide the feedback required for ve

researcharxiv-cs-ro

The Lattice of Transition Laws

arXiv:2610.11216v1 Announce Type: cross Abstract: Diffusion and autoregression (AR) have long been seen as different categories of generative models, with diffusion specialising in continuous fields a

The optimal information complexity of VC learning

arXiv:2610.10600v1 Announce Type: cross Abstract: Steinke and Zakynthinou(2020) introduces the Conditional Mutual Information (CMI) framework of analyzing the information complexity of learning algori

The Sample Complexity of Membership Inference and Privacy Auditing

arXiv:2508.19458v2 Announce Type: replace Abstract: A membership-inference attack gets the output of a learning algorithm, and a target individual, and tries to determine whether this individual is a

Thought-Like-Pro: Enhancing Reasoning of Large Language Models through Self-Bootstrapped Prolog-based Chain-of-Thought

arXiv:2407.14562v3 Announce Type: replace Abstract: Large language models have demonstrated remarkable capabilities as general-purpose assistants, excelling in a wide range of reasoning tasks and supp

Toward Joint Optimization of Circuit Depth and Training Data Size in Adaptively Grown Quantum Classifiers

arXiv:2610.12428v1 Announce Type: cross Abstract: Building a quantum model involves a tradeoff: how complex the circuit should be, and how much training data it needs. Caro et al. show that models wit

Toward Lunar Legged Robots: Field Deployment Lessons at LUNA

arXiv:2610.12276v1 Announce Type: new Abstract: Legged robots are promising candidates for future lunar surface missions because they can traverse steep, loose, and obstacle-rich terrain that challeng

researcharxiv-cs-ro

Transferability of Learned States in Neural PDE Solvers

arXiv:2610.10972v1 Announce Type: new Abstract: Assessing useful reuse in neural PDE solvers is challenging: final accuracy can reflect source learning and target-time computation. Our reuse contract

Transformed Samplers with Variance Reduction

arXiv:2610.10870v1 Announce Type: cross Abstract: Markov chain Monte Carlo (MCMC) methods are the standard tool for computing expectations under complex probability distributions. Control variates red

Transforming Image Editors into Video Editors

arXiv:2610.11037v1 Announce Type: new Abstract: Recent image editing systems have achieved impressive semantic understanding, visual fidelity, and instruction-following ability, while video editing re

Transmission Neural Networks: Inhibitory and Excitatory Connections

arXiv:2604.04246v2 Announce Type: replace-cross Abstract: This paper extends the Transmission Neural Network model proposed by Gao and Caines in [1]-[3] to incorporate inhibitory connections and neuro

Type-Checking for Pattern-Based Tree Transformations

arXiv:2610.11337v1 Announce Type: cross Abstract: We introduce and study pattern-based tree transformations. As an illustrating example, consider a source pattern (x dot y) + (x dot z) and a target pa

Understanding Latent-Dimension Scaling in Dynamical-System Learning through Spectral Reliability

arXiv:2610.11866v1 Announce Type: new Abstract: In deep learning, approximation theory motivates increasing representation size. We ask whether this benefit extends to dynamics learning through autore

Using Weisfeiler-Leman Features for Algorithm Selection in Constraint Optimisation

arXiv:2610.12119v1 Announce Type: cross Abstract: Algorithm Selection is essential for efficient Constraint Programming. Over the years, many algorithm selectors based on machine learning methods have

UXBench Pro: Benchmarking Personalized User Experience in Multi-Turn Dialogue Interactions

arXiv:2610.11638v1 Announce Type: new Abstract: Evaluating user experience (UX) with automated computational methods has gained increasing attention, supported by empirical evidence from UXBench. Howe

V-CoLA: Vision Token Compression with Linear Attention

arXiv:2610.11251v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated impressive capabilities but suffer from substantial computational overhead, as vision tokens dominate th