Search: “research”

Perceptual Quality Loss or Loss of Perceptual Quality?

arXiv:2609.35054v1 Announce Type: cross Abstract: Contemporary deep speech enhancement (SE) models are often trained with specific auxiliary terms in the loss function as a way to improve their perfor

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Phase Space Attention:A Hairer Lift Circumvents the Single-Layer Induction Obstruction

DGX agent

arXiv:2609.32319v1 Announce Type: new Abstract: We circumvent the Sanford-Hsu-Telgarsky (SHT) single-layer induction obstruction within a linear, one-step, causal, bilinear, symplectically consistent

researcharxiv-cs-lg

29 Sept 2026

Phenomenon-Graph JEPA: Label-Efficient Representation Learning for Contactless Cardiorespiratory Sensing

arXiv:2609.32928v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar and RGB-D cameras can record cardiac and respiratory waveforms continuously and without contact, but labeled recordings r

Physics-Informed Neural Networks for Depth-Averaged Avalanche Dynamics

arXiv:2609.34916v1 Announce Type: cross Abstract: Accurate prediction of avalanche motion is essential for hazard assessment in mountainous terrain. This study develops and evaluates a physics-informe

PIC-UIE: Predicting Image-Adaptive Corrections for Lightweight Underwater Image Enhancement

arXiv:2609.33318v1 Announce Type: new Abstract: Underwater image enhancement (UIE) aims to restore visibility, color fidelity, and structural detail from images degraded by wavelength-dependent attenu

Plan-to-Synthesis: Cross-City Human Mobility Generation via Semantic Latent Flow Matching

arXiv:2609.32732v1 Announce Type: cross Abstract: Human mobility generation aims to synthesize realistic point-of-interest (POI) visitation trajectories and has become an important tool for travel beh

Poly-attention: a general scheme for higher-order self-attention

arXiv:2602.02422v2 Announce Type: replace Abstract: The self-attention mechanism, at the heart of the Transformer model, is able to effectively model pairwise interactions between tokens. However, num

Polylogarithmic Nash Regret in Matrix Games with Bandit Feedback

arXiv:2609.34812v1 Announce Type: new Abstract: We study Nash regret minimization in unknown finite matrix games with bandit payoff feedback and observed opponent actions. We develop Optimistic Payoff

PORTER: Edge-Cloud Residency for Persistent 3D Scene Graph Memory

arXiv:2609.33258v1 Announce Type: cross Abstract: Recent task-driven and just-in-time 3D Scene Graph (3DSG) methods reduce per-task representations by constructing or activating only task-relevant inf

Positions Are Not Facts: The Mismatch Between KV Caches and Memory

arXiv:2609.33759v1 Announce Type: cross Abstract: When a fact changes, how should a language model update the history stored in its key-value (KV) cache? Hiding the old record is cheap, but it may sti

Posterior Regimes and Latent Deception: Variational Bayesian Inference in Hidden Markov Models for Sequential Fraud Detection in Financial Transactions

arXiv:2609.34031v1 Announce Type: new Abstract: We present a three-tier progression of Hidden Markov Models: maximum-likelihood (Baum-Welch), variational Bayesian (VBEM), and a neural variational exte

PQR3D: Progressive Query Refinement over Reference-Conditioned Temporal Windows for Multi-View 3D Object Detection

arXiv:2609.32163v1 Announce Type: new Abstract: Temporal context is essential for camera-only multi-view 3D object detection. Existing streaming detectors maintain and propagate query states from one

Precise Editing and Flexible Referencing for Interactable Worlds

arXiv:2609.34470v1 Announce Type: new Abstract: We present EditWorld, a video world model for precise editing and flexible referencing in interactable worlds. Existing video world models primarily foc

Predicting the Next State Is Not Enough: JEPA Representations for Lean Theorem Proving

arXiv:2609.32908v1 Announce Type: new Abstract: Neural theorem provers must both propose tactics and decide which valid successor states to explore. We study whether one-step Lean transitions provide

Prediction Limits and Koopman Closure of Geometry-Induced Soft State Abstractions

arXiv:2609.32652v1 Announce Type: cross Abstract: We study when geometry-induced soft state abstractions admit accurate finite-dimensional linear dynamics. Each state is represented by simplex-valued

Preserving DEG Rankings for Gene Discovery in Histology-Based Spatial Gene Expression Prediction

arXiv:2609.33928v1 Announce Type: new Abstract: Predicting spatial gene expression from histology images could scale spatial transcriptomics (ST) to image-only cohorts, but conventional histology-base

Pretraining Transformers with Quantized Softmax in Attention

arXiv:2609.33591v1 Announce Type: new Abstract: Low-precision Transformer systems increasingly quantize attention matrix multiplications, while softmax often remains at higher precision. During pretra

Printability-Constrained Adversarial Decals for Near-Nadir Aerial Perception: Measured Ink Gamuts, Nested Realism Constraints, and a Physical-World Bound

arXiv:2609.33513v1 Announce Type: new Abstract: Adversarial patches for aerial perception are typically evaluated as digital composites, with printing left as an implementation detail. This study impo

Proactive Motion Planning for Human-Robot Cooperation

arXiv:2609.32354v1 Announce Type: new Abstract: This abstract addresses the incorporation of human motion prediction into proactive and dynamic human-aware motion planning, with the goal of enabling s

researcharxiv-cs-ro

Probabilistic Geodesic Flow Matching on Location-Scale Families

arXiv:2609.34613v1 Announce Type: cross Abstract: Flow matching (FM) has recently emerged as a promising framework for generative modeling due to its conceptual simplicity and strong empirical perform

ProDyGS: Dynamic Gaussian Splatting from a Single Static Monocular Camera

arXiv:2609.32711v1 Announce Type: new Abstract: We present ProDyGS, a novel dynamic 3D Gaussian Splatting framework for high-quality novel view synthesis from videos captured by a single static camera

Progressive Risk Estimation for Accident Anticipation

arXiv:2609.32811v1 Announce Type: new Abstract: Accident anticipation aims to recognize anomalous driving cues before a crash while avoiding false alarms during normal driving. Existing approaches typ

Prompt-Anchored Residual Adaptation for Biomedical Vision-Language Models

arXiv:2609.33701v1 Announce Type: new Abstract: Pretrained biomedical vision-language models achieve strong zero-shot performance in biomedical image classification. However, downstream biomedical cla

Prompting Particle Physics: Tokenized Multi-modal Foundation Models for Combinatorially Many Tasks

arXiv:2609.31862v1 Announce Type: cross Abstract: Reconstruction and simulation at a collider experiment are long chains of specialised algorithms, each tuned to a single step. We explore how one mode

Propagate, Then Sharpen: Post-Hoc Refinement of Frozen Node Classifiers

arXiv:2609.35080v1 Announce Type: new Abstract: We study post-hoc refinement of frozen node classifiers: given only the graph G and class distributions Q predicted by a frozen model, can we improve ac

Prosodic ABX: A Language-Agnostic Method for Measuring Prosodic Contrast in Speech Representations

arXiv:2604.02102v2 Announce Type: replace-cross Abstract: Speech representations from self-supervised speech models (S3Ms) are known to be sensitive to phonemic contrasts, but their sensitivity to pro

Protected Cores Are Not Enough: Certifying AI-Proposed Revisions of Temporal Specifications

arXiv:2609.33461v1 Announce Type: cross Abstract: Runtime monitoring traditionally evaluates a specification that is fixed before execution or externally modified when requirements change. In learning

ProtoSeam: Lifting Classifier Training with Latent Gaussian Mixture Models

arXiv:2609.35174v1 Announce Type: new Abstract: We propose a lifted reformulation of supervised classification that improves the final accuracy of standard classifiers without changing the architectur

Proxy2World: Learning to Generate Worlds From Lightweight Proxies without Seeing Them

arXiv:2609.35023v1 Announce Type: new Abstract: Lightweight scene proxies let creators control scene layout and motion while leaving room for imagination in appearance, lighting, and visual effects. H

Pulseflow: PPG Counterfactual Generation Via Latent Transport

arXiv:2609.33501v1 Announce Type: new Abstract: Photoplethysmography (PPG) has become an important modality for continuous cardiovascular monitoring, including atrial fibrillation (AF) detection. Howe

Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization

arXiv:2509.22161v4 Announce Type: replace Abstract: Vector quantization, which discretizes a continuous vector space into a finite set of representative vectors (a codebook), has been widely adopted i

QSCP: Beyond Class-Name Prompts for Query-Guided Semantic Change Parsing

arXiv:2609.33088v1 Announce Type: new Abstract: Traditional change detection (CD) identifies changes between bi-temporal remote sensing images, while semantic change detection (SCD) assigns predefined

QuacamFM: Quaternion-Constrained Flow Matching for Camera Pose Estimation

arXiv:2609.32455v1 Announce Type: new Abstract: Camera pose estimation from multi-view images remains a challenge in computer vision. Traditional methods often address this problem using Structure-fro

Quality Determines Direction, Length Shapes Magnitude: Length Control for Open-Ended Reinforcement Learning

arXiv:2609.34718v1 Announce Type: new Abstract: Reinforcement learning (RL) changes not only what language models say, but also how much they say, often increasing response length at the cost of token

Quantization Error Is Spectrally Flat: A Single Random Probe Is a Calibrated, Data-Free Sensitivity Estimator, with Application to Budget-Targeted Mixed-Precision Quantization

arXiv:2609.33923v1 Announce Type: cross Abstract: A single random Gaussian probe gives an unbiased estimate of the squared Frobenius norm of a layer's quantization error. The estimator is well-behaved

Query Expansion and Key Specialization in Transformer Attention Geometry

arXiv:2609.34273v1 Announce Type: cross Abstract: The projection of queries and keys are central to the attention mechanism in Transformer architectures. While they are mathematically symmetric, they

R2T: Rule-Encoded Loss Functions for Sequence Tagging in Low-Resource Languages

arXiv:2510.13854v2 Announce Type: replace-cross Abstract: We introduce Rule-to-Tag (R2T), a framework that turns linguistic rules into the training signal for neural sequence taggers in low-resource l

Reachability is not enough: Diagnosing long-range behavior in GNNs

arXiv:2609.33674v1 Announce Type: new Abstract: Graph neural networks (GNNs) are often called long-range because their architecture can connect distant nodes, but this does not show whether they use d

RECAST: Recasting Vision-Language Semantics into an Actionable Cost Map for Robot Navigation

arXiv:2609.32595v1 Announce Type: new Abstract: Safe and robust robot navigation across diverse environments requires a high-level understanding of complex scenes and the ability to carry it into stab

researcharxiv-cs-ro

Re:Cognize -- Open-Set Comic Character Re-Identification

arXiv:2609.34032v1 Announce Type: new Abstract: A manga reader meets a character on one page and knows them on sight a hundred pages later, without ever being handed a cast list. Re-identifying comic

Recovering Lower-Dimensional Semialgebraic Support of a Measure from its Moments

arXiv:2609.33420v1 Announce Type: cross Abstract: Recovering probability measures from their moments has numerous applications, esp. in connection with the method of moments in statistics and optimiza

Recursive LLM Degradation in Biomedical Question Answering: A Cross-Generation Study

arXiv:2609.34257v1 Announce Type: cross Abstract: Repeatedly training language models on their own generated data may create a synthetic-data feedback loop in which errors and distributional biases ar

ReDrive: Shaping Representations with World Modeling for End-to-End Driving

arXiv:2609.33854v1 Announce Type: new Abstract: Driving policies require capabilities of scene understanding and future evolution prediction. To achieve this goal, current end-to-end models typically

Reduce, Then Encode: Multiscale Volumetric Reduction for 2D Foundation Models in Brain MRI

arXiv:2609.35405v1 Announce Type: new Abstract: Pretrained 2D foundation models offer a practical alternative to dedicated 3D pretraining for brain structural magnetic resonance imaging (sMRI), but th

Reference-Tail Trust:Certified Probability Floors for Learned Updates Inside a Deployed Network

arXiv:2609.34904v1 Announce Type: new Abstract: Graph neural networks (GNNs) need to exploit improved message passing without surrendering control over predictions already trusted in deployment. We in

Refinement Symmetry in Multimodal Transformers

arXiv:2609.32669v1 Announce Type: cross Abstract: Attention weights depend on token counts, which change with the representation of a signal. We study refinement symmetry: splitting a representation w

ReFM: Semantic-Aware Refinement Flow Model for Motion Retargeting

arXiv:2609.32068v1 Announce Type: new Abstract: Motion retargeting transfers motion across characters with different skeletal structures while preserving semantic intent and physical plausibility. Des

Region-Local Copula Evidence Fusion for Heterogeneous Remote Sensing Change Detection

arXiv:2609.32716v1 Announce Type: new Abstract: Superpixel copula models provide stable regional evidence for heterogeneous remote sensing change detection, but a single label per region limits locali