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Physiological Noise Augmentation Improves Non-Invasive Brain-to-Speech

arXiv:2607.05165v1 Announce Type: new Abstract: Non-invasive brain-to-speech decoding aims to restore communication to patients suffering from neurodegenerative disease, without the risks of neurosurg

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Piecewise Dynamic Diffusion Regularization for Reconstruction of Cardiac Cine MRI

DGX agent

arXiv:2607.03299v1 Announce Type: cross Abstract: Real-time cardiac cine MRI enables visualization of the beating heart during free breathing, but severe undersampling and motion make reconstruction h

researcharxiv-cs-cv

7 Jul 2026

Piercing Gilbreath's Conjecture: From Deep Number Theory Insights to Fintech and Cybersecurity

arXiv:2607.04166v1 Announce Type: cross Abstract: I propose a new methodology to attack the fascinating Gilbreath's conjecture about prime numbers, first posted in 1878 and unsolved to this day. The p

PixCon: Clean-Positive Contrastive Learning for Foundation-Model Semi-Supervised Segmentation

arXiv:2607.03068v1 Announce Type: cross Abstract: Semi-supervised semantic segmentation (SSSS) has long turned on one question, which pseudo-labels to trust, and answered it with ever more careful con

PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space

arXiv:2607.05373v1 Announce Type: new Abstract: 3D reconstruction and generation are commonly tackled by separate paradigms: pixel-based regression for reconstruction, and latent diffusion for generat

Platonic Projection Structures: Operator-Induced Observability in Representation Learning

arXiv:2607.05175v1 Announce Type: new Abstract: We characterize observability in representation learning through Platonic Projection Structures (PPS), an operator-theoretic framework for analyzing rep

PLoRA: Efficient Concurrent LoRA Training for Large Language Models

arXiv:2508.02932v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has gained popularity as a fine-tuning approach for Large Language Models (LLMs) due to its low resource requirements and

PotatoGANs: Utilizing Generative Adversarial Networks, Instance Segmentation, and Explainable AI for Enhanced Potato Disease Identification and Classification

arXiv:2405.07332v2 Announce Type: cross Abstract: Numerous applications have resulted from the automation of agricultural disease segmentation using deep learning techniques. However, when applied to

PraMem: Practice-derived Experiential Memory for Long-horizon Behavior Prediction

arXiv:2607.02881v1 Announce Type: new Abstract: Long-horizon behavior prediction aims to infer a user's next action based on a lengthy historical sequence, playing a crucial role in artificial intelli

Predicting the Emergence of Induction Heads in Language Model Pretraining

arXiv:2511.16893v3 Announce Type: replace Abstract: Specialized attention heads dubbed induction heads (IHs) have been argued to underlie the remarkable in-context learning capabilities of modern lang

Predicting Therapeutic Outcome via Aligning Patient-Specific Knowledge Graph and Gene-Level Perturbation Representations

arXiv:2607.04557v1 Announce Type: cross Abstract: Accurate prediction of patient-specific therapeutic response from pre-treatment transcriptomes is hindered by the scarcity of matched clinical respons

PreSIST: Vision-Language-Informed Object Persistence Prediction in Open-World Scenes

arXiv:2607.04057v1 Announce Type: new Abstract: Robots deployed over long periods must reason about environments that change over time. Existing long-term perception systems often address object chang

Pretreatment MRI reveals a latent, molecular-subtype-independent structural phenotype that organizes treatment trajectories and recurrence risk

arXiv:2607.02768v1 Announce Type: cross Abstract: Pathologic complete response and tumor shrinkage measure whether breast cancer responds to neoadjuvant therapy, but not whether that response was stru

Prior Diffusiveness and Regret in the Linear-Gaussian Bandit

arXiv:2601.02022v2 Announce Type: replace Abstract: We prove that Thompson sampling exhibits ilde{O}(sigma d sqrt{T} + d r sqrt{Tr(Sigma_0)}) Bayesian regret in the linear-Gaussian bandit with a N(mu_

Privacy-Preserving Industrial Ergonomics: mmWave-Based Automated REBA Scoring and Pose Estimation

arXiv:2607.02611v1 Announce Type: new Abstract: Work-related Musculoskeletal Disorders (WMSDs) require continuous ergonomic assessments. While Rapid Entire Body Assessment (REBA) is a gold-standard ob

Privacy-Preserving Robustness Verification for Neural Networks

arXiv:2607.05251v1 Announce Type: cross Abstract: Neural network verification and data privacy are inherently in tension: verification demands full access to model parameters and input data, yet both

Probably Correct Optimal Stable Matching under Two-Sided Uncertainty

arXiv:2607.04824v1 Announce Type: new Abstract: We study a sequential learning problem for stable matchings in two-sided markets where preferences on both sides are initially unknown. We focus on a ce

Probe-EM: Targeted Neuron Tracing via Training-Free Semantic Verification

arXiv:2607.04696v1 Announce Type: new Abstract: Establishing large-scale, high-resolution neural connectivity maps is fundamental to elucidating the structural basis of brain function. However, when p

Probing Low-Level Acoustic Attribute Encoding in CLAP Audio Embeddings

arXiv:2607.03806v1 Announce Type: cross Abstract: Audio foundation models are widely adopted as general-purpose feature extractors, yet the internal structure of their learned representations remains

ProCon: Projection-Consistency Memory for Training-Free Anomaly Detection

arXiv:2607.04894v1 Announce Type: new Abstract: Memory-based anomaly detection is attractive because it localizes defects from normal images without training a decoder or synthesizing pseudo anomalies

Programming over Thinking: Efficient and Robust Multi-Constraint Planning

arXiv:2601.09097v3 Announce Type: replace Abstract: Multi-constraint planning involves identifying, evaluating, and refining candidate plans while satisfying multiple, potentially conflicting constrai

Progressive Refinement: An Iterative Pseudo-Labeling Approach for Mandarin-English Code-Switching ASR

arXiv:2607.05224v1 Announce Type: new Abstract: Code-switching (CS), alternating languages within the same utterance, poses significant challenges for automatic speech recognition (ASR) due to limited

ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space

arXiv:2607.02907v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but still struggle with complex visual reasoning tasks requiring multi-step

Property-Constrained 3D Porous Media Reconstruction from 2D Images via Conditional Generative Adversarial Networks

arXiv:2607.02693v1 Announce Type: new Abstract: This study presents a conditional Generative Adversarial Network (cGAN) framework for generating 3D porous media volumes with controlled porosity, train

ProPS: Prompted Profile Synthesis for Natural Language-Conditioned Speaker Embedding Distributions

arXiv:2607.05276v1 Announce Type: cross Abstract: Speaker embeddings, or x-vectors, are widely used to represent speaker identity and speaker-related attributes, but existing embedding extractors are

Provable Pruning for Efficient 3D Gaussian Splatting via Coresets

arXiv:2607.02721v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables high-quality real-time novel-view synthesis, but practical scenes often contain millions of Gaussians, making compr

psytechlab at CLPsych 2026: Utilising Natural Language Processing methods and Large Language Models for Social Media Text Analysis

arXiv:2607.03003v1 Announce Type: new Abstract: Social media posts are a rich and valuable source of data for analyzing mental health states and users' well-being using automated analysis tools. In th

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference

arXiv:2511.04805v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models have shown strong potential in scaling language models efficiently by activating only a small subset of expert

Q-TriM: Question-Guided Tri-Modal Attention for Audio-Visual Question Answering

arXiv:2607.03825v1 Announce Type: cross Abstract: Audio-Visual Question Answering (AVQA) extends classical VQA by requiring joint reasoning over video and synchronized audio. However, many AVQA system

Qantara: Bridge-Flow Training for Multi-Paradigm JEPA Control

arXiv:2607.04978v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) underpin a growing family of latent world models for control from raw pixels, but every existing JEPA

Quadrature-Aware Complex-Linear Neural Operator for Boundary-to-Field Prediction in Resonant Acoustics

arXiv:2607.04407v1 Announce Type: cross Abstract: Repeated prediction of acoustic fields from spatially distributed boundary excitation is computationally expensive when each source realization requir

Quantum-Inspired Harmonic Decision Models: A Computational Framework for Music Generation

arXiv:2607.05007v1 Announce Type: new Abstract: This paper introduces a quantum-inspired computational framework for harmonic decision-making in music. The proposed approach formulates harmonization a

Quantum Kolmogorov--Arnold representation theorem for continuous unitary-valued maps

arXiv:2607.03187v1 Announce Type: cross Abstract: The classical Kolmogorov--Arnold representation theorem states that any continuous multivariate function can be exactly decomposed into a finite compo

Quantum Spectral Anomaly Detection

arXiv:2607.05307v1 Announce Type: cross Abstract: A core task in quantum anomaly detection is to compute an anomaly score that quantifies how strongly a test quantum state deviates from a given quantu

Quick ViTs: Speeding up Vision Transformers through Equivariance

arXiv:2505.15441v5 Announce Type: replace-cross Abstract: Natural images exhibit strong geometric regularities: local structures, such as edges, corners, and textures, appear in many orientations and

Quickest Detection of Hallucination Onset: Delay Bounds and Learned CUSUM Statistics

arXiv:2606.12476v3 Announce Type: replace-cross Abstract: Token-level hallucination detectors are evaluated as classifiers, by AUC over all tokens, yet a streaming monitor is judged by its reaction ti

Rank-Order N-of-M Codes for Sparse Distributed Memory: Disentangling Representation and Learning Effects in Noise Robustness Against Contemporary Neuromorphic Architectures

arXiv:2607.02967v1 Announce Type: new Abstract: Large language models remain limited as continual learning systems, motivating renewed interest in Sparse Distributed Memory (SDM) as an explicit online

Rating the Pitch, Not the Product: User Evaluations of LLMs Reflect Expectations More Than Performance

arXiv:2607.05113v1 Announce Type: new Abstract: Imagine two users interact with the same LLM. One has been told it is the cutting-edge flagship model; the other, an older, weaker model. They walk away

Real-Time LiDAR Gaussian Splatting SLAM

arXiv:2607.04127v1 Announce Type: new Abstract: We present a real-time LiDAR-based framework for Gaussian Splatting SLAM that tightly couples fast G-ICP registration with spherical rasterization-based

Reconstructing Rational Functions on Finite Abelian Groups with Higher Autocorrelations

arXiv:2503.21022v2 Announce Type: replace Abstract: The higher-order autocorrelations of integer-valued or rational-valued functions on finite Abelian groups appear naturally in X-ray crystallography,

Recursive Entropic Variational Inference for Nonlinear State-Space Models

arXiv:2511.15409v2 Announce Type: replace Abstract: We present a class of algorithms for state estimation in nonlinear, non-Gaussian state-space models. Our approach is based on a variational Lagrangi

Reduced-Order Models: The Mother of World Models

arXiv:2607.03198v1 Announce Type: new Abstract: World models -- compressed latent representations of an environment that support action-conditioned prediction and planning -- are typically presented a

Reflected Schrodinger Bridge Matching

arXiv:2607.03626v1 Announce Type: new Abstract: Recent advances in generative modeling have enabled the efficient computation of Schrodinger bridges (SB) in high-dimensional settings by leveraging par

Reliability-Aware Monocular Depth Supervision for Sparse-View Neural Reconstruction

arXiv:2607.02554v1 Announce Type: new Abstract: Sparse-view neural reconstruction is challenging in outdoor driving scenes, where cameras usually move along a narrow forward-facing trajectory and prov

Replicability is Asymptotically Free in Multi-armed Bandits

arXiv:2402.07391v3 Announce Type: replace-cross Abstract: We consider a replicable stochastic multi-armed bandit algorithm that ensures, with high probability, that the algorithm's sequence of actions

Representation Recycling for Streaming Video Analysis

arXiv:2204.13492v5 Announce Type: replace Abstract: We present StreamDEQ, a method that aims to infer frame-wise representations on videos with minimal per-frame computation. Conventional deep network

Representing and Detecting Label Ambiguity in IMU-Based Exercise Evaluation

arXiv:2607.04842v1 Announce Type: new Abstract: Home-based physiotherapy is performed without supervision, which leads to incorrect execution and motivates systems that assess movement automatically f

Repurposing CLIP to Localize at Pixel Level

arXiv:2607.05253v1 Announce Type: new Abstract: Large-scale Vision-Language Models like CLIP have demonstrated impressive open-set localization capabilities at the image level. However, adapting this