Search: “research”

From Learner Behavior to Reusable Skills for Effective and Efficient Learner Simulation

arXiv:2609.37157v1 Announce Type: new Abstract: Learner simulation aims to reproduce how a particular learner behaves on new tasks. Although Large Language Models (LLMs) can generate increasingly fine

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Research

From Seeds to Semantics: Measuring Semantic Accessibility in Deterministic Diffusion Models

DGX agent

arXiv:2602.06155v2 Announce Type: replace Abstract: Diffusion models generate samples through a sequence of learned denoising steps, and recent work has studied how semantic structure appears along th

researcharxiv-cs-lg

30 Sept 2026

From Sky to Soil: A Morphing Aerial-Ground Robot for Seed Deployment

arXiv:2609.37072v1 Announce Type: new Abstract: Aerial seed broadcasting can reach remote restoration sites, but provides limited control over seed placement within the soil. This paper presents a geo

researcharxiv-cs-ro

Fundamental Limits of Transferability and Equivariance in Algebraic Signal Models I: Finite Dimensions

arXiv:2609.36106v1 Announce Type: cross Abstract: We study the fundamental limits of transferability in algebraic signal processing through homomorphisms between algebraic signal models. Homomorphisms

GA-EIRFS: A Geometry-Augmented Repeat-Factor Sampling Method for Long-Tailed LiDAR 3D Object Detection

arXiv:2609.38116v1 Announce Type: new Abstract: Long-tailed 3D object detection is treated as a class-frequency problem, but LiDAR supervision quality depends on object observability: similar frequenc

Generalizable Lifelong Model Editing via Preference Optimization

arXiv:2609.36748v1 Announce Type: new Abstract: Knowledge editing enables rapid updates of specific factual knowledge in large language models (LLMs) without full retraining. However, more realistic s

Generated Query Expansion Still Helps Strong Sparse Retrieval: A Controlled Study with SPLADE-v3

arXiv:2609.37911v1 Announce Type: cross Abstract: Scientific queries are often brief, while relevant papers use specialized vocabulary. Generated query expansion can bridge this mismatch, but earlier

Geometry-Aided Channel Deduction with Partial Channel Estimates and Uncalibrated Digital Twin

arXiv:2609.37277v1 Announce Type: cross Abstract: The acquisition of high-dimensional channel state information (CSI) in wireless MIMO-OFDM communications usually requires high pilot overhead, or reli

Geometry-Conditioned Fixed-Scaffold Encoders for Time-Warp Robust Sequence Retrieval

arXiv:2609.36809v1 Announce Type: new Abstract: Embedding-based retrieval is attractive for long sequence collections because each item can be encoded once and searched by nearest-neighbor ranking. Th

GeoSET: Generalist Foundation Model for SAR-to-EO Image Translation

arXiv:2609.37496v1 Announce Type: new Abstract: Paired synthetic aperture radar (SAR) and electro-optical (EO) imagery is increasingly available across sensors, resolutions, and geographic regions. Ye

GLASS: Global Latent Aggregation with Slot-based Set Decoding for Scalable All-Atom Crystal Generation

arXiv:2609.37158v1 Announce Type: new Abstract: Generative models for crystals enable the discovery of novel structures, but scaling all-atom generation to larger systems such as metal--organic framew

GlassFormer: Learning Real-time Glass Segmentation using Radar-Depth Fusion

arXiv:2609.36844v1 Announce Type: new Abstract: Transparent surfaces are ubiquitous in built environments, yet they remain a persistent failure case for robotic perception. RGB cameras perceive the ba

GNA: Granular Neighbor Assembly for Retrieval-Augmented Multivariate Time-Series Forecasting

arXiv:2609.36281v1 Announce Type: new Abstract: Deep forecasters predict from a fixed-length lookback window, and lengthening it gives diminishing returns at a growing cost. Retrieval augmentation ins

Grab a Coffee: Future-Aware Guidance for Discrete Diffusion with Compiled Objectives

arXiv:2609.35924v1 Announce Type: new Abstract: Discrete diffusion models generate sequences by iteratively resolving multiple tokens in parallel, offering a flexible alternative to left-to-right gene

Graph neural networks for sampling-invariant embeddings of organized signal sets

arXiv:2609.35934v1 Announce Type: cross Abstract: Sensor networks and radars can deliver signals as organized sets, e.g. ordered signals, signals describing range cells within a grid or signals percei

Graph-Spectral Flow Matching for Multivariate Time Series Anomaly Detection

arXiv:2609.36765v1 Announce Type: new Abstract: Multivariate time series anomaly detection typically relies on evaluating discrepancies between observations and outputs produced by models trained on n

GraphVQ: Structure-Aware Autoregressive Decoding over Context-Quantized Graph Tokens

arXiv:2609.37604v1 Announce Type: new Abstract: Graph foundation models need a discrete token representation, but casting a graph as a generatable token sequence faces a structural obstacle: edges spa

GRFBrain: Graph-Structured Rectified Flows for EEG Dynamic Modeling

arXiv:2609.37934v1 Announce Type: new Abstract: Forecasting time-varying functional connectivity from electroencephalography (EEG) requires modeling both history-dependent trends and structured variab

GUITAR: Structured Failure Diagnosis of GUI Agents via State Transitions

arXiv:2609.34113v2 Announce Type: replace Abstract: Understanding where and why Graphical User Interface (GUI) agents fail is essential for building more reliable systems, yet current evaluation relie

HARMONI: Aligning Human and Scene Priors for Multi-View 4D Reconstruction

arXiv:2603.12789v3 Announce Type: replace Abstract: Recent advances in 3D foundation models have enabled joint reconstruction of humans and their surrounding environments. However, combining independe

Hidden Reasoning Must Leak, but Need Not Be Readable: Fundamental Opportunities and Limits for Chain-of-Thought Monitoring

arXiv:2609.37312v1 Announce Type: cross Abstract: Can reasoning models trick chain of thought (CoT) monitors and perform hidden computation without revealing it in their thinking traces? We show that

Hierarchical Utility Calibration for Structured Multiclass Decisions

arXiv:2609.36532v1 Announce Type: cross Abstract: In multiclass probabilistic prediction, Utility Calibration (UC), which focuses auditing on specified utilities, has recently received attention as a

High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching

arXiv:2609.37037v1 Announce Type: new Abstract: High-resolution dynamic functional connectivity (DFC) can reveal rapidly evolving brain-network interactions, but short temporal windows yield noisy, of

Honeycomb: Constant-Size Scene Memory Representation for Video World Models

arXiv:2609.37690v1 Announce Type: new Abstract: Video world models require persistent scene memory to maintain consistency during long-horizon video generation. Existing spatial memory systems accumul

How Medical VLMs Underutilize Their Vision Encoders: A Dermatology Perspective

arXiv:2609.36557v1 Announce Type: cross Abstract: Medical Vision-Language Models (VLMs) show significant promise for clinical image understanding, offering accurate diagnosis with interpretable reason

Human-AI Collaboration: From Paradoxes to Patterns

arXiv:2609.36481v1 Announce Type: new Abstract: Evidence shows that humans and AI systems perform better together, by collaborating, than alone. This paper examines two key design dimensions of human-

Human-inspired, Task-Dimension-Guided Exploration for Efficient Learning in High Dimensions

arXiv:2609.36672v2 Announce Type: new Abstract: Efficient exploration in high-dimensional decision spaces remains a central challenge for decision-making systems. Humans, in contrast, can navigate lar

Hybrid Ensemble Learning for EEG-Based Epileptic Seizure Forecasting

arXiv:2609.35876v1 Announce Type: new Abstract: Epileptic seizure forecasting aims to provide actionable warnings before seizure onset, yet patient-independent generalization and false-alarm control r

Hybrid Feature Learning for Handwriting Verification

arXiv:1812.02621v2 Announce Type: replace Abstract: We propose an effective Hybrid Deep Learning (HDL) architecture for the task of determining the probability that a questioned handwritten word has b

Hybrid Neural Simulation-Based Inference for Robust Applications and Limited-Budget Scenarios

arXiv:2609.36044v1 Announce Type: cross Abstract: We develop two hybrid techniques that approach the performance of neural simulation-based inference (NSBI) analyses while substantially reducing the c

HyDI: A hybrid Deep Learning-Inductive Logic Programming ensemble for multi-label classification

arXiv:2609.37740v1 Announce Type: new Abstract: While attaining remarkable results for many applications, Deep Learning models are notoriously difficult to explain. This work introduces HyDI, a hybrid

Hyper Yoshimura: How a slight tweak on a classical folding pattern unleashes meta-stability for deployable robots

arXiv:2505.09919v3 Announce Type: replace Abstract: Deployable structures inspired by origami have provided lightweight, compact, and reconfigurable solutions for various robotic and architectural app

researcharxiv-cs-ro

HyperSAM: A Promptable Foundation Model for Hyperspectral Remote Sensing

arXiv:2609.37340v1 Announce Type: new Abstract: Hyperspectral remote sensing provides dense spectral measurements that are indispensable for material-level Earth observation, yet the construction of a

Hyperspherical Semantic Trajectory Analysis: Mapping Technological Diffusion across Academic Preprints, Patent Signals, and Compute Scaling

arXiv:2609.35845v1 Announce Type: new Abstract: Macroeconomic productivity metrics, such as Total Factor Productivity, register technological breakthroughs with multi-year reporting lags due to admini

researcharxiv-cs-cl

HyperZip: Efficient Data Compression through Personalized Diffusion LLMs with Hypernetworks

arXiv:2609.36357v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for lossless data compression, but existing approaches are constrained by the high computationa

Identifying ODEs from Unstructured Data with Causal Representation Learning

arXiv:2609.37083v1 Announce Type: cross Abstract: We study the problem of recovering the governing ODE of a dynamical system from unstructured, high-dimensional observations such as images. Existing m

Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering

arXiv:2609.38177v1 Announce Type: cross Abstract: Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs h

researcharxiv-cs-cl

Implementing Cumulative Functions with Generalized Cumulative Constraints

arXiv:2508.01751v3 Announce Type: replace Abstract: Modeling scheduling problems with conditional time intervals and cumulative functions has become a common approach when using modern commercial cons

Improved Distributional Diffusion Models

arXiv:2609.37147v1 Announce Type: new Abstract: Distributional Diffusion Models (DDMs) replace the standard mean-prediction denoiser with a distributional denoiser trained via a scoring rule objective

Inferring Soil Friction Angle from Robot Foot-Ground Force Histories: A Bayesian Inverse Approach to Proprioceptive Soil Sensing

arXiv:2609.36582v1 Announce Type: new Abstract: Foot-ground interaction signals recorded by quadruped robots may enable spatially distributed, in situ characterization of soil strength. As a first ste

researcharxiv-cs-ro

Information-theoretic receding-horizon active learning of nonlinear dynamical systems

arXiv:2609.36712v1 Announce Type: cross Abstract: Accurately learning nonlinear dynamics from a finite-duration experiment requires the efficient collection of informative data. We address this challe

InsightMap: Structured Spatial Modeling for Embodied Multimodal Reasoning

arXiv:2609.37187v1 Announce Type: new Abstract: Language-guided navigation requires connecting partial observations to a persistent spatial reference and learning how actions change that representatio

Inter-patient ECG Arrhythmia Classification with LGNs and LUTNs

arXiv:2601.11433v2 Announce Type: replace Abstract: Deep Differentiable Logic Gate Networks (LGNs) and Lookup Table Networks (LUTNs) are demonstrated to be suitable for the automatic classification of

Interpretable intrinsic dimension estimation through componentwise calibration of distance and angle

arXiv:2609.37114v1 Announce Type: new Abstract: DANCo (Dimensionality from Angle and Norm Concentration) jointly calibrates nearest-neighbor distance and angular statistics and consistently reaches st

Into the danger zone: stable extrapolation in high-dimensional function and operator learning

arXiv:2609.36709v1 Announce Type: cross Abstract: Out-of-distribution (OOD) generalization is a central challenge in scientific machine learning. We study regression problems in which the test distrib

Intrinsic Associative Memory on Riemannian Manifolds: Curvature, Capacity, and Emergent Modes

arXiv:2609.35948v1 Announce Type: cross Abstract: Geometry does more than constrain an associative memory: curvature determines what it remembers and which states it creates. We develop intrinsic dens

It's All Training: A Fully Synthetic Single-Stage Recipe for LLMs

arXiv:2609.37891v1 Announce Type: new Abstract: Current pre-training datasets are derived from web crawls, with all their issues, and were not designed to support mid- and post-training pipelines--for

researcharxiv-cs-cl

It's Not What the Image Shows: Irrelevant Context Destabilises VLM Judges Without Informing Them

arXiv:2609.37863v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used in place of human annotators, making it important that substitutability tests reflect the model ra