Search: “research”

FormulaSPIN: Self-Play Fine-Tuning for Natural Language to Spreadsheet Formula Generation

arXiv:2607.19354v1 Announce Type: new Abstract: Spreadsheet applications are used by hundreds of millions worldwide, yet writing formulas remains a significant barrier. Existing approaches rely on sta

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From Bit-Position Sensitivity to Unequal Error Protection for DNN Inference Memory

DGX agent

arXiv:2607.19623v1 Announce Type: cross Abstract: We characterize per-bit-position fault sensitivity in ML inference across 16 workloads -- spanning transformer-based models and attention-free CNNs --

researcharxiv-cs-lg

23 Jul 2026

Gaze-DETR: Top-Down Guidance Through Priority Maps for Infrared Weak-Small UAV Detection with DETR

arXiv:2607.19040v1 Announce Type: new Abstract: Infrared small target detection (ISTD) remains challenging because tiny, low-contrast targets are easily overwhelmed by clutter, noise, or occlusion. Co

Generalized Kalman filter based temporal difference reinforcement learning

arXiv:2607.20010v1 Announce Type: new Abstract: In this paper, we present a generalized temporal-difference (TD) reinforcement learning framework based on the theory of conditional expectations. The v

Generating Bearing Vibration Signals at User-Specified Fault Probabilities Using PR-GAN and Counterfactual Methods

arXiv:2607.19455v1 Announce Type: new Abstract: In bearing vibration datasets, most samples receive predicted fault probabilities close to 0 or 1, while samples with intermediate (gray-zone) probabili

Generative AI floods and dilutes the market for books

arXiv:2607.20349v1 Announce Type: cross Abstract: Generative AI can produce book-length works of fiction at near-zero cost. These books are often dismissed as low-quality ``slop'' that buyers will ign

Generative World Renderer at the Speed of Play

arXiv:2607.18703v1 Announce Type: new Abstract: Generative world renderer AlayaRenderer receives structured world states exported from physics engines and synthesizes RGB frames. Unlike models that ge

Geometric Attention: A Regime-Explicit Operator Semantics for Transformer Attention

arXiv:2601.11618v2 Announce Type: replace-cross Abstract: Geometric Attention (GA) specifies an attention layer by four independent inputs: a finite carrier (what indices are addressable), an evidence

Geospatial Diffusion-based Evolution Synthesis (GeoDES) for Storm-Centered Weather Augmentation

arXiv:2607.19522v1 Announce Type: new Abstract: While machine learning-based weather models hold significant promise, they struggle to predict the detailed structure of large-scale weather systems suc

Gotta Catch them all: the modes of Sycophancy

arXiv:2607.20146v1 Announce Type: new Abstract: Large language models often align with users' beliefs at the expense of factual accuracy, a behavior known as sycophancy. Prior mechanistic studies larg

Group-of-Latents: Perceptual Video Compression at Extreme Bitrates via Masked Latent Generative Modeling

arXiv:2607.19437v1 Announce Type: cross Abstract: Most existing video compression algorithms follow a paradigm of transformation and quantization, optimizing the trade-off between distortion and bitra

H^2SD: Hybrid Hindsight Self-Distillation

arXiv:2607.18955v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) provides reliable outcome supervision for language model reasoning, but a scalar traject

Hard Guarantees at a Measured Price: Entropy-Stable Learned Finite Volumes for Compressible Flow

arXiv:2607.20171v1 Announce Type: cross Abstract: Learned solvers for compressible flow are usually compared to classical methods at equal mesh resolution rather than at equal computational cost, and

HeadCast: Casting Attention Heads for Efficient Autoregressive Video Generation

arXiv:2607.20125v1 Announce Type: cross Abstract: Autoregressive (AR) video diffusion models have become a promising paradigm for long and streaming video synthesis, but the continuously growing Key-V

HijackKV: New Threat in Position-Independent KV Cache Reuse

arXiv:2607.19957v1 Announce Type: cross Abstract: Key-Value (KV) cache reduces inference latency in large language models (LLMs). Traditional prefix-based reuse has low cache hit rates across inferenc

How Does Urban Context Relate to Residential Building Health? A Vision-POI Fusion Framework for Building-Level Housing Inspection

arXiv:2607.20263v1 Announce Type: new Abstract: Housing-level urban physical examination is essential for identifying residential building problems and supporting targeted urban renewal. Existing auto

Hybrid LSTM-Graph Neural Framework for Robust Financial Fraud Detection and Adversarial Resilience

arXiv:2607.19350v1 Announce Type: new Abstract: Financial institutions face significant challenges in detecting sophisticated money laundering patterns, such as smurfing and layering, due to extreme d

IConE: Batch Independent Collapse Prevention for Self-Supervised Representation Learning

arXiv:2603.15263v2 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) has revolutionized representation learning, with Joint-Embedding Architectures (JEAs) emerging as an effective

Identity-Paired Progressive Depth Training: When Trainability Persists Beyond Expressibility

arXiv:2607.16800v2 Announce Type: replace-cross Abstract: Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, yet their training suffers from sensitivity to c

Image Editing Models are Numerical Solvers

arXiv:2607.18787v1 Announce Type: new Abstract: We investigate whether a pretrained generative image-editing model can provide a common interface for numerical simulation. Physical inputs and solution

InstructMixup: Instruction-Guided Salient Patch Editing for Robust Data Augmentation

arXiv:2607.19324v1 Announce Type: new Abstract: In image and video technologies, data augmentation is widely used to improve the generalization of deep visual models, and mixup-based strategies that i

Integrity of peer-to-peer distributed LLM inference under malicious nodes

arXiv:2607.19490v1 Announce Type: cross Abstract: Peer-to-peer distributed inference executes a Large Language Model (LLM) on pooled consumer hardware by spreading its layers across many nodes. Every

Juxtaposition of Shallow Reservoir-Triggered Seismicity and Deep Tectonic Locking in the Qiaojia-Dongchuan Seismic Gap

arXiv:2607.19606v1 Announce Type: cross Abstract: Identifying the critical state of mature seismic gaps is challenging, especially when anthropogenic stress perturbations, such as reservoir impoundmen

Kernel Ridge Regression Inference

arXiv:2302.06578v4 Announce Type: replace-cross Abstract: We provide uniform confidence bands for kernel ridge regression (KRR), a widely used nonparametric regression estimator for nonstandard data s

Kontinuous Kontext: Continuous Strength Control for Instruction-based Image Editing

arXiv:2510.08532v2 Announce Type: replace Abstract: Instruction-based image editing offers a powerful and intuitive way to manipulate images through natural language. Yet, relying solely on text instr

Label-Free Finite-Volume-Residual Training of Attention Graph Neural Networks for Coupled Thermo-Fluid Fields

arXiv:2607.20321v1 Announce Type: cross Abstract: Neural surrogates are widely used in scientific machine learning for fast prediction of three-dimensional (3D) thermo-fluid fields. However, generatin

LaCache: Exact Caching and Precision-Adaptive Inference for Diffusion Large Language Models

arXiv:2607.16339v2 Announce Type: replace Abstract: Diffusion-based Large Language Models(DLLMs) enable parallel generation via Semi-Autoregressive (SAR) decoding in text generation. However, current

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models

arXiv:2607.19120v1 Announce Type: new Abstract: Geometric foundation models, such as the Visual Geometry Grounded Transformer (VGGT), provide strong 3D priors from unposed images. However, such models

LC-SLab -- An object-based deep learning framework for large-scale land cover classification from satellite imagery and sparse in-situ labels

arXiv:2509.15868v2 Announce Type: replace Abstract: Large-scale land cover maps generated using deep learning play a critical role across a wide range of Earth science applications. Open in-situ datas

Learning the Arabic Dialect Continuum as a Continuous Space: A Regression Approach to Speaker Origin Prediction

arXiv:2607.19751v1 Announce Type: cross Abstract: We present a regression-based approach to Arabic dialect geolocation that models dialectal variation as a continuous geographic space rather than disc

Lifted Representation Hypothesis in Language Models

arXiv:2607.19360v1 Announce Type: new Abstract: Large language models (LLMs) often answer queries by mapping individual observations to more general rule-like structures. However, it remains unclear h

Machine Can Automatically Discover Parametric Functions to Model HEP Data

arXiv:2607.19750v1 Announce Type: cross Abstract: In HEP data analyses, finding an adequate function to model binned data has largely relied on a manual process: guess a functional form by intuition,

Machine-learned syndrome post-selection for reliable quantum error correction

arXiv:2607.19563v1 Announce Type: cross Abstract: Quantum error correction can be enhanced by post-selecting out runs that are likely to produce a logical failure, but the most accurate measures for t

Memo2496: Expert-Annotated Dataset and Dual-view Adaptive Framework for Music Emotion Recognition

arXiv:2512.13998v4 Announce Type: replace-cross Abstract: Music Emotion Recognition (MER) is constrained by limited expert annotations and the need to establish robustness across heterogeneous corpora

Memory-Augmented Multimodal Large Language Models for Small Object Understanding in Streaming Aerial Videos

arXiv:2607.19857v1 Announce Type: cross Abstract: Language-guided aerial perception aims to understand user-specified tiny targets in complex unmanned aerial vehicle (UAV) scenes. In real UAV deployme

Morphing MILR: Design and control of a cable-driven limbless robot with rolling joints for maneuvering in complex environments

arXiv:2607.19714v1 Announce Type: new Abstract: Limbless robots offer exceptional mobility in confined and cluttered environments due to their slender bodies and their ability to exploit body-terrain

researcharxiv-cs-ro

Multi-Mask Diffusion Language Models for Few-Step Generation

arXiv:2607.19686v1 Announce Type: new Abstract: Masked diffusion models (MDMs) are a promising family of language generators, but achieving high-quality few-step generation remains challenging. In MDM

Multi-Resolution Voxelized Map-Based Stereo Visual-Inertial Odometry

arXiv:2607.17332v2 Announce Type: replace Abstract: Incorporating prior maps significantly enhances the accuracy and robustness of pose estimation in visual-inertial odometry (VIO). However, the large

researcharxiv-cs-ro

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?

arXiv:2607.20284v1 Announce Type: new Abstract: The rapid development of multimodal large language models (MLLMs) has introduced a flexible paradigm for remote sensing image scene understanding (RSISU

MVGD-Net: A Novel Motion-aware Video Glass Surface Detection Method

arXiv:2601.13715v2 Announce Type: replace Abstract: Glass surface ubiquitous in both daily life and professional environments presents a potential threat to vision-based systems, such as robot and dro

Non-Asymptotic Variational Learning for Monotone Nonlinear Multiscale Elliptic Equations: Scale-Robust Primal-Dual Bounds and Strong-Form Statistical Ill-Conditioning

arXiv:2607.15702v2 Announce Type: replace-cross Abstract: We develop a non-asymptotic approximation, sampling, and finite-iteration optimization theory for variational physics-informed approximation o

Notes to Self: Can LLMs Benefit from Experiential Abstractions?

arXiv:2607.20372v1 Announce Type: new Abstract: Humans distill experience into reusable abstractions, e.g., strategies and cautionary reminders, and apply them to gradually solve problems more effecti

Now We Know? A Systematic Comparison of TerraMind and THOR

arXiv:2607.18504v1 Announce Type: cross Abstract: Benchmarks for Geospatial Foundation Models (GFMs) increasingly rank models by aggregate score, but such rankings obscure why models differ: how much

Nuclear Quantum Effects as a Denoising Problem

arXiv:2607.19680v1 Announce Type: cross Abstract: Nuclear quantum effects are rigorously captured by imaginary-time path integrals, which map the quantum Boltzmann distribution onto a ring polymer of

Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention

arXiv:2607.18112v2 Announce Type: replace Abstract: Panoptic segmentation in complex scenes remains challenging because of occlusions, yet modern approaches often neglect occlusion modelling. In this

On Optimization Complexity of Second-Order Certified Unlearning

arXiv:2607.20192v1 Announce Type: new Abstract: We study machine unlearning: the removal of memorized training data from a trained model. Specifically, we investigate the algorithmic complexity of cer

On the Separability of Information in Diffusion Models

arXiv:2509.23937v5 Announce Type: replace-cross Abstract: Diffusion models transform noise into data by injecting information that was captured in their neural network during the training phase. In th

Online Optimization of Difference-of-Convex Compositions with Smooth Mappings

arXiv:2607.19553v1 Announce Type: cross Abstract: We study online optimization for a broad class of structured non-convex non-smooth problems where each loss is a composition of a difference-of-convex