Search: “research”

On Computing Total Variation Distance Between Mixtures of Product Distributions

arXiv:2605.03839v1 Announce Type: cross Abstract: We study the problem of approximating the total variation distance between two mixtures of product distributions over an n-dimensional discrete domain

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On the Invariants of Softmax Attention

DGX agent

arXiv:2605.02907v1 Announce Type: new Abstract: Softmax attention maps every query--key interaction into a probability distribution, but the underlying structure remains largely unexplored. We define

researcharxiv-cs-lg

6 May 2026

On the Privacy of LLMs: An Ablation Study

arXiv:2605.02255v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in interactive and retrieval-augmented settings, raising significant privacy concerns. While at

Optimization of CV-QKD Under Practical Constraints

arXiv:2605.02045v1 Announce Type: cross Abstract: Using reinforcement learning, we optimize for practical hardware constraints, including limited FIR filter taps at the transmitter and receiver, mean

Optimizing Grasping in Legged Robots: A Deep Learning Approach to Loco-Manipulation

arXiv:2508.17466v3 Announce Type: replace-cross Abstract: This paper presents a deep learning framework designed to enhance the grasping capabilities of quadrupeds equipped with arms, with a focus on

Ortho-Hydra: Orthogonalized Experts for DiT LoRA

arXiv:2605.03252v1 Announce Type: cross Abstract: LoRA fine-tuning of diffusion transformers (DiT) on multi-style data suffers from style bleed: a single low-rank residual cannot represent several dis

Over 10 million Americans will lose health care coverage because of Republican cuts to Medicaid and Obamacare subsidies. That amounts to hal…

Over 10 million Americans will lose health care coverage because of Republican cuts to Medicaid and Obamacare subsidies. That amounts to half of the total number of people who gained health insurance

Parametrizing Convex Sets Using Sublinear Neural Networks

arXiv:2605.03520v1 Announce Type: cross Abstract: We propose a neural parameterization of convex sets by learning sublinear (positively homogeneous and convex) functions. Our networks implicitly repre

Partial-differential-algebraic equations of nonlinear dynamics by Physics-Informed Neural-Network: (I) Operator splitting and framework assessment

arXiv:2408.01914v4 Announce Type: replace-cross Abstract: Several forms for constructing novel physics-informed neural-networks (PINN) for the solution of partial-differential-algebraic equations base

Partial Effective Information Decomposition for Synergistic Causality

arXiv:2605.03267v1 Announce Type: cross Abstract: Causality is a central topic in scientific inquiry, yet for complex systems, the identification and analysis of synergistic causation remain a challen

Partially Observed Structural Causal Models

arXiv:2605.03268v1 Announce Type: new Abstract: Here we introduce Partially Observed Structural Causal Models (POSCMs) that formalize causal systems where latent contexts co-determine both the interac

PerFlow: Physics-Embedded Rectified Flow for Efficient Reconstruction and Uncertainty Quantification of Spatiotemporal Dynamics

arXiv:2605.03548v1 Announce Type: new Abstract: Reconstructing PDE-governed fields from sparse and irregular measurements is challenging due to their ill-posed nature. Deterministic surrogates are tra

Permutation-Consensus Listwise Judging for Robust Factuality Evaluation

arXiv:2603.20562v2 Announce Type: replace Abstract: Large language models (LLMs) are now widely used as judges, yet their decisions can change under presentation choices that should be irrelevant. We

PHALAR: Phasors for Learned Musical Audio Representations

arXiv:2605.03929v1 Announce Type: cross Abstract: Stem retrieval, the task of matching missing stems to a given audio submix, is a key challenge currently limited by models that discard temporal infor

Phoneme-Level Deepfake Detection Across Emotional Conditions Using Self-Supervised Embeddings

arXiv:2605.03079v1 Announce Type: cross Abstract: Recent advances in emotional voice conversion (EVC) have enabled the generation of expressive synthetic speech, raising new concerns in audio deepfake

Pose Tracking with a Foundation Pose Model and an Ensemble Directional Kalman Filter

arXiv:2605.03105v1 Announce Type: new Abstract: This paper introduces the ensemble directional Kalman filter (EnDKF), an ensemble-based Kalman filtering approach for pose tracking that jointly estimat

Position: How can Graphs Help Large Language Models?

arXiv:2605.02452v1 Announce Type: new Abstract: With the rapid advancement of large language models (LLMs), classic graph learning tasks have greatly benefited from LLMs, including improved encoding o

(POSTER) From Sensors to Insight: Rapid, Edge-to-Core Application Development for Sensor-Driven Applications

arXiv:2605.02844v1 Announce Type: cross Abstract: Scientists increasingly rely on sensor-based data; however transforming raw streams into insights across the edge-to-cloud continuum remains difficult

Posterior-First Neural PDE Simulation: Inferring Hidden Problem State from a Single Field

arXiv:2605.03247v1 Announce Type: new Abstract: Neural PDE simulators often receive only a single observed field at deployment. In this setting, a field-to-future predictor can collapse distinct laten

Predicting Euler Characteristics and Constructing Topological Structure Using Machine Learning Techniques

arXiv:2605.02947v1 Announce Type: new Abstract: This study proposes a novel approach to extract topological properties, specifically the Euler characteristic, from input images using neural networks w

Prediction horizon shapes representations in predictive learning

arXiv:2511.09290v2 Announce Type: replace Abstract: Predictive learning has emerged as a central paradigm for training models across diverse data domains and is increasingly viewed as a foundation for

President Biden made health insurance more affordable for millions of Americans in the ACA marketplace. The Republicans’ actions increased p…

President Biden made health insurance more affordable for millions of Americans in the ACA marketplace. The Republicans’ actions increased prices by 58% on average—amounting to huge extra costs for th

Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs

arXiv:2605.03964v1 Announce Type: new Abstract: Training machine learning interatomic potentials (MLIPs) for reactive chemistry is often bottlenecked by the high cost of quantum chemical labels and th

Proteo-R1: Reasoning Foundation Models for De Novo Protein Design

arXiv:2605.02937v1 Announce Type: new Abstract: Deep learning in de novo protein design has achieved atomic-level fidelity. However, existing models remain largely non-deliberative: they directly synt

Provable Accuracy Collapse in Embedding-Based Representations under Dimensionality Mismatch

arXiv:2605.03346v1 Announce Type: cross Abstract: Embedding-based representations in Euclidean space R^d are a cornerstone of modern machine learning, where a major goal is to use the smallest dimensi

Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution

arXiv:2505.00334v3 Announce Type: replace Abstract: Image Super-Resolution is a fundamental problem in computer vision with broad applications spacing from medical imaging to satellite analysis. The a

Random test functions, H^{-1} norm equivalence, and stochastic variational physics-informed neural networks

arXiv:2605.03542v1 Announce Type: cross Abstract: The dual norm characterisation of weak solutions of second-order linear elliptic partial differential equations is mathematically natural but computat

Realizable Bayes-Consistency for General Metric Losses

arXiv:2605.03823v1 Announce Type: new Abstract: We study strong universal Bayes-consistency in the realizable setting for learning with general metric losses, extending classical characterizations bey

Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models

arXiv:2605.02912v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) has traditionally been framed as binary classification or outlier detection, providing neither interpretable reasoning nor

Red states have disproportionately benefited from the health insurance subsidies expanded by Biden and then cut by Trump. Georgia is a clear…

Red states have disproportionately benefited from the health insurance subsidies expanded by Biden and then cut by Trump. Georgia is a clear example: in just one year, marketplace enrollment has dropp

Reliable AI Needs to Externalize Implicit Knowledge: A Human-AI Collaboration Perspective

arXiv:2605.02010v1 Announce Type: new Abstract: This position paper argues that reliable AI requires infrastructure for human validation of implicit knowledge. AI learns from both explicit knowledge (

Repurposing and Evaluating the (In)Feasibility of Dataset Poisoning enabled Watermarking for Contrastive Learning

arXiv:2605.01834v1 Announce Type: cross Abstract: Contrastive learning (CL) reduces annotation cost via auto-derived supervisory signals. Since large-scale in-house CL datasets are infeasible, relianc

Reservoir property image slices from the Groningen gas field for image translation and segmentation

arXiv:2605.03942v1 Announce Type: new Abstract: Reservoir characterization workflows increasingly rely on image-based and machine-learning/deep learning or even generative AI approaches, but openly av

Rethinking Explanations: Formalizing Contrast in Description Logics

arXiv:2605.01442v1 Announce Type: new Abstract: There has been a growing interest in explaining entailments over description logic (DL) knowledge bases. The existing explanation formalisms focus on ju

Rethinking Temporal Consistency in Video Object-Centric Learning: From Prediction to Correspondence

arXiv:2605.03650v1 Announce Type: new Abstract: The de facto approach in video object-centric learning maintains temporal consistency through learned dynamics modules that predict future object repres

RFKjr == Lyssenko

Yann LeCun compares RFK Jr. to Trofim Lysenko, the Soviet biologist whose pseudoscientific theories caused agricultural disaster, suggesting RFK Jr. promotes similarly discredited or anti-scientific i

Rose-SQL: Role-State Evolution Guided Structured Reasoning for Multi-Turn Text-to-SQL

arXiv:2605.03720v1 Announce Type: new Abstract: Recent advances in Large Reasoning Models (LRMs) trained with Long Chain-of-Thought have demonstrated remarkable capabilities in code generation and mat

Scaling Laws and Symmetry, Evidence from Neural Force Fields

arXiv:2510.09768v2 Announce Type: replace Abstract: We present an empirical study in the geometric task of learning interatomic potentials, which shows equivariance matters even more at larger scales;

Scoring Edit Impact in Grammatical Error Correction via Embedded Association Graphs

arXiv:2604.06573v2 Announce Type: replace Abstract: A Grammatical Error Correction (GEC) system produces a sequence of edits to correct an erroneous sentence. The quality of these edits is typically e

Semantically Enriching Investor Micro-blogs for Opinion-Aware Emotion Analysis: A Practical Approach

arXiv:2605.03092v1 Announce Type: new Abstract: While sentiment analysis is the staple of financial NLP, capturing the nuances of 'why' behind that sentiment remains a challenge. There have been attem

Sensorless State Estimation and Control for Agile Cable-Suspended Payload Transport by Quadrotors

arXiv:2605.03666v1 Announce Type: new Abstract: This work proposes a novel control and estimation approach for aerial manipulation of a cable-suspended load using Unmanned Aerial Vehicles (UAVs). Comm

researcharxiv-cs-ro

Sentiment Analysis of Indonesian Spotify Reviews Using Machine Learning and BiLSTM

arXiv:2605.03443v1 Announce Type: new Abstract: This paper benchmarks classical machine learning and deep learning approaches for three-class sentiment classification of Indonesian Spotify reviews. Us

Skeleton-Snippet Contrastive Learning with Multiscale Feature Fusion for Action Localization

arXiv:2512.16504v3 Announce Type: replace Abstract: The self-supervised pretraining paradigm has achieved great success in learning 3D action representations for skeleton-based action recognition usin

Sparse Data Tree Canopy Segmentation: Fine-Tuning Leading Pretrained Models on Only 150 Images

arXiv:2601.10931v2 Announce Type: replace Abstract: Tree canopy detection from aerial imagery is an important task for environmental monitoring, urban planning, and ecosystem analysis. Simulating real

Spatiotemporal Convolutions on EEG signal -- A Representation Learning Perspective on Efficient and Explainable EEG Classification with Convolutional Neural Nets

arXiv:2605.03874v1 Announce Type: new Abstract: Classification of EEG signals using shallow Convolutional Neural Networks (CNNs) is a prevalent and successful approach across a variety of fields. Most

Spectral- and Energy-efficient Multi-BS Multi-RIS Pinching-antenna Systems: A GNN-based Approach

arXiv:2605.01307v1 Announce Type: cross Abstract: This paper investigates coordinated downlink transmission in a multi-base station (multi-BS) multi-reconfigurable intelligent surface (multi-RIS)-assi

Speculative Coupled Decoding for Training-Free Lossless Acceleration of Autoregressive Visual Generation

arXiv:2510.24211v2 Announce Type: replace Abstract: Autoregressive (AR) modeling has recently emerged as a promising new paradigm in visual generation, but its practical adoption is severely constrain

Speculative Speculative Decoding

arXiv:2603.03251v3 Announce Type: replace Abstract: Autoregressive decoding is bottlenecked by its sequential nature. Speculative decoding has become a standard way to accelerate inference by using a