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Enhancing Transformer Representations of Symbolic ODE Expressions

arXiv:2609.24746v1 Announce Type: new Abstract: Existing approaches to solving differential equations, such as symbolic regression, physics informed neural networks, and neural operators, typically fo

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Error-Supervised Synthetic Learner Writing for Automated Essay Scoring

DGX agent

arXiv:2609.23573v1 Announce Type: new Abstract: Synthetic essays can help reduce dependence on human-written data in Automated Essay Scoring (AES). However, they often lack realistic errors, limiting

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22 Sept 2026

ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining

arXiv:2505.19893v2 Announce Type: replace-cross Abstract: Large language model pretraining is compute-intensive, yet many tokens contribute marginally to learning, resulting in inefficiency. We introd

Estimating Accurate Hand Pose in Camera Space with Vision Transformer

arXiv:2609.24424v1 Announce Type: new Abstract: Monocular RGB-based hand pose estimation has emerged as a critical research frontier in computer vision. The local hand pose estimation methods predict

Estimation and Control of Tensegrity Manipulator Kinematics based on Strut Inclination Angles

arXiv:2609.24535v1 Announce Type: new Abstract: Unlike conventional rigid-link robots defined by discrete joints, continuum robots pose a fundamental challenge for expressing their complex continuous

Event Signature Transfer: Model-Agnostic Forecast Scenario Construction from Historical Events

arXiv:2609.23074v1 Announce Type: cross Abstract: Forecasters often know an event is imminent but not the shape, size, or timing of its effect. We introduce Event Signature Transfer (EST), a training-

Exact Quotients of Fresnel-Kummer Surfaces and Certified Biaxial Refraction

arXiv:2609.23249v1 Announce Type: new Abstract: The Fresnel wave surface governs the propagation of light in a transparent biaxial crystal. It is a special Kummer quartic, and we identify it exactly.

Exactness at Inference: A Representational Criterion for Out-of-Distribution Generalization

arXiv:2609.24942v1 Announce Type: new Abstract: A model generalizes outside its training distribution only when it computes a representation structurally equivalent to the generating mechanism, not an

Experimental Evaluation of a Low-Power Ultra-Wideband Receiver for Spectrum Sensing

arXiv:2609.22134v1 Announce Type: cross Abstract: Walsh-sequence-based receiver architectures offer an alternative approach for the reception and reconstruction of multiple simultaneous RF signals ove

Expert-Play Contouring Control: Faster-than-Demonstration Planning from Slow Expert and Fast Play

arXiv:2609.22798v1 Announce Type: new Abstract: Expert demonstrations often specify what a robot should do, but not how fast it can do it. Imitation Learning (IL) inherits demonstration timing, while

Exponential Family Synthetic Controls

arXiv:2609.23970v1 Announce Type: cross Abstract: We develop exponential family synthetic controls (EFSC), a distributional version of synthetic controls for a panel of datasets. Each cell of the pane

Extracting Arguments, Not Just Classifying Them: Instruction-Tuned LLMs for Generative Component Detection

arXiv:2609.24855v1 Announce Type: cross Abstract: Argumentative component detection (ACD) is a core subtask of Argument(ation) Mining (AM) and one of its most challenging aspects, as it requires joint

Fast Graph Laplacian Estimation using Effective Resistance

arXiv:2609.23668v1 Announce Type: cross Abstract: Inferring network topology from noisy node observations is a central problem in graph signal processing. In this paper, we consider Laplacian-constrai

Feasibility Distance Fields for Heterogeneous Constraints in Robot Configuration Space

arXiv:2609.24632v1 Announce Type: new Abstract: Robot manipulators are monitored by constraint-specific indicators whose units and gradient scales are not comparable, so they do not provide a common m

Feature Suppression and Differential Privacy for Residential Traffic Classification: A Two-Home Federated Study

arXiv:2609.23521v1 Announce Type: new Abstract: Residential traffic classification supports service management, but learning across homes must account for heterogeneous traffic and privacy constraints

Financial Language Models as Applied Artificial Intelligence Systems for News-Based Trading under Market Frictions

arXiv:2609.23703v1 Announce Type: new Abstract: Financial language models can transform unstructured firm-specific news into structured decision signals, but financial AI research lacks an integrated

Finite Topological Space Filtrations: A Topological Framework for Data Analysis

arXiv:2512.23348v3 Announce Type: replace-cross Abstract: We introduce a data-analysis framework based on filtrations of finite topological spaces. Starting from a finite metric data set, we construct

FinsSim: A Reality-Aligned Integrated Simulation Platform for Underwater Robot Learning

arXiv:2609.23943v1 Announce Type: new Abstract: Underwater robot learning relies on simulators that integrate high-fidelity hydrodynamics, convenient learning interfaces, and a credible transition to

Forecasting Intrathecal Tracer Enhancement from Pre-Contrast Brain MRI: Direct Regression versus Flow Matching

arXiv:2609.22377v1 Announce Type: cross Abstract: Intrathecal contrast-enhanced MRI tracks how a cerebrospinal-fluid tracer spreads through the brain, but requires repeated scans over 24--48,h. Foreca

From Articles to Publishers: Aggregating Language Model Predictions for News Source Reliability Inference

arXiv:2609.24219v1 Announce Type: new Abstract: Traditionally, the reliability of news publishers is assessed by expert organisations that evaluate editorial practices, transparency and factual standa

From Latent Biomarkers to Clinical Rules: Embedding-Guided Rule Mining and Attribution-Based Translation for Interpretable Tabular Learning

arXiv:2609.22155v1 Announce Type: new Abstract: Clinical decision support tools are most useful when accurate predictions are accompanied by understandable explanations. Rule-based models provide tran

From Noise to Signal: When Outliers Seed New Topics

arXiv:2603.18358v2 Announce Type: replace Abstract: Outliers in dynamic topic modeling are typically treated as noise, yet we show that some can serve as early signals of emerging topics. We introduce

From Outliers to Topics in Language Models: Anticipating Trends in News Corpora

arXiv:2509.22030v2 Announce Type: replace Abstract: This paper examines how outliers, often dismissed as noise in topic modeling, can act as weak signals of emerging topics in dynamic news corpora. Us

From Regional to Global: Transfer Learning for Atmospheric Transport Emulators

arXiv:2609.23838v1 Announce Type: new Abstract: Greenhouse gas emissions estimates can be derived using inverse methods by combining atmospheric concentration observations with chemical transport mode

From Tables to Quantified Statements: Evaluating LLM Inference Generation through Executable Verification

arXiv:2609.23966v1 Announce Type: new Abstract: LLMs can generate fluent descriptions from tables, but their outputs may remain logically unsupported by the structured data. We introduce STAT-TO-TEXT,

GAE: Learning a Geometry-Native Latent Space for 3D-Consistent World Generation

arXiv:2609.24981v1 Announce Type: new Abstract: We present a compact geometry-native latent space as a shared foundation for perception and generation. Visual generators can produce photorealistic fra

GAPS: Generative Active Pseudo-view Selection for Sparse-View 3D Gaussian Splatting

arXiv:2609.23436v1 Announce Type: new Abstract: Novel view synthesis from sparse observations is severely under-constrained. Although 3D Gaussian Splatting (3DGS) enables real-time rendering, it produ

GenVoid: Uncertainty-Aware Learning of Subsurface Material Defects with an Experimentally Validated Physics-Informed Generative Model

arXiv:2609.23761v1 Announce Type: new Abstract: Internal voids are ubiquitous defects in manufactured structures, yet their characterization remains challenging because their geometry is hidden and ca

GeoBalance: Geometry-Aware Monitoring and Reconstruction with Asymmetric Optimization for Balanced Multimodal Learning

arXiv:2609.23533v1 Announce Type: new Abstract: Multimodal classifiers can converge to modality-dominant solutions in which one modality dominates the joint prediction, suppressing the learning of oth

GLR-MM: Graph-Based Global-Local Reconstruction for Robust Multimodal Chest X-ray and EHR Representation Learning under Missing Modalities

arXiv:2609.23876v1 Announce Type: new Abstract: Clinical multimodal models must often predict before all chest X-ray (CXR) and electronic health record (EHR) inputs are available. Existing approaches

GNN-based Path-aware multi-view Circuit Learning for Technology Mapping

arXiv:2601.14286v2 Announce Type: replace-cross Abstract: Traditional technology mapping suffers from systemic inaccuracies in delay estimation due to its reliance on abstract, technology-agnostic del

GPLQ: A General, Practical, and Lightning QAT Method for Vision Transformers

arXiv:2506.11784v2 Announce Type: replace Abstract: Vision Transformers (ViTs) are essential in computer vision but are computationally intensive, too. Model quantization, particularly to low bit-widt

GrapeSplat: Geometry-Grounded Reconstruction via Amalgamated Pose-Free Encoding for Feed-Forward 3D Gaussian Splatting

arXiv:2609.23182v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting now reconstructs renderable scenes from unposed, uncalibrated images. Yet, most models supervise only photometric con

Graph Learning for Cross-Subject, Cross-Population EEG Emotion Decoding and Model-Derived Spatial-Spectral Neural Signatures

arXiv:2609.22103v1 Announce Type: cross Abstract: Electroencephalography (EEG) provides a noninvasive means of capturing emotion-related neural dynamics, yet reliable EEG emotion decoding lacks models

Graph-to-Grid (G2G): Continuous-Coordinate Feature Painting for Soccer Pass Surfaces

arXiv:2609.24040v1 Announce Type: cross Abstract: Dense pass surfaces give, for every pitch cell, whether a pass played there would arrive, whether the carrier would choose it, and what the possession

GraphSVR: q-Space--Aware Graph-Based Slice-to-Volume Registration for Diffusion MRI

arXiv:2609.24732v1 Announce Type: new Abstract: Diffusion-weighted imaging (DWI) remains highly vulnerable to subject motion, particularly in time-efficient protocols and in motion-prone populations.

GraphToolbox: A Configurable Python Framework for Graph Neural Network Forecasting

arXiv:2609.24609v1 Announce Type: new Abstract: Electricity forecasting often involves spatially related signals observed over regions, substations, and feeders, and Graph Neural Networks (GNNs) provi

GRRR: The Geometry of Reshaping, Rotation, and Routing in Decoder LLM post-training

arXiv:2609.22146v1 Announce Type: cross Abstract: We study how post-training changes the weights of Large Language Models (LLMs) relative to their pretrained weights. Across 12 post-training chains wi

Guaranteed Low-Rank Tensor Recovery from Modewise Measurements via Normalized Block-Weighted Riemannian Gradient Descent

arXiv:2609.24679v1 Announce Type: new Abstract: We consider the recovery of low-multilinear-rank tensors from linear measurements and propose an adaptive block-weighted modewise Riemannian gradient de

H-Spec: Parallel Speculative Decoding Without a Drafter-Side KV Cache

arXiv:2609.24197v1 Announce Type: new Abstract: Speculative decoding losslessly accelerates large language model inference by having a lightweight draft model predict future tokens for verification by

H-VLA: Hierarchical Vision-Language-Action Model with Key-Action Reasoning and Motion Planning in a Unified Action Space

arXiv:2609.22895v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but many existing methods still rely on direct mappings from l

HEARTH: An Object-Centric RGB-Thermal-3D Dataset for Temperature-Aware Robot Manipulation

arXiv:2609.23418v1 Announce Type: new Abstract: Language-guided manipulation can depend on physical properties that visible appearance does not reveal. Temperature is one such property, but object dat

Helix-FNO: Spectral-Domain Operator Learning Coupled with a High-Fidelity Mechanistic Model for Fast Surrogate Simulation

arXiv:2609.22129v1 Announce Type: new Abstract: Mechanistic simulation models of full-scale treatment processes remain the only trustworthy, extrapolative description of the underlying physico-chemica

Hierarchical Aggregation of Semantic Uncertainty in 3D Scene Graphs

arXiv:2609.22351v1 Announce Type: new Abstract: Open-vocabulary 3D Scene Graphs (3DSGs) ground each object node in a vision-language embedding, yet they record every entry as equally certain, so a rob

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning?

arXiv:2412.07813v4 Announce Type: replace-cross Abstract: To alleviate the training burden in federated learning while enhancing convergence speed, Split Federated Learning (SFL) has emerged as a prom

Human-LLM Deliberation as Interactive Proof: Conditions for Verifiability Without Transparency

arXiv:2609.24895v1 Announce Type: new Abstract: When an LLM supplies an argument that a user could not readily construct, how can the user decide whether to accept its claim? Inspired by interactive p

HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants

arXiv:2509.08494v2 Announce Type: replace-cross Abstract: As humans delegate more tasks and decisions to artificial intelligence (AI), we risk losing control of our individual and collective futures.

Hybrid Uncertainty Sensitivity Analysis Based on the HSIC for High-Dimensional Responses with Aleatory--Epistemic Separation

arXiv:2606.14053v2 Announce Type: replace-cross Abstract: Quantifying the influence of hybrid aleatory and epistemic uncertainties on high-dimensional system responses remains a major challenge in glo