Search: “research”

STRUCTURALCOST: A controlled reading time dataset for modeling human sentence processing difficulty

arXiv:2610.08208v1 Announce Type: cross Abstract: We introduce STRUCTURALCOST, a self-paced reading dataset of 475 participants and 40,800 observations isolating the processing cost of long-distance s

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Supermarket Product Detection and Recognition: Utilizing Deep Learning with Rectified Imagery

DGX agent

arXiv:2610.08126v1 Announce Type: cross Abstract: Product Identification has sprung up to become one of the most challenging problems in the automation of the retail industry. With the new industry 5.

researcharxiv-cs-ai

7 Oct 2026

SURGE: Sonar-fUsed Reconstruction and localization via image-gated Graph Estimation

arXiv:2610.07472v1 Announce Type: new Abstract: Remotely operated vehicles (ROVs) are widely used to explore and inspect underwater environments such as caves, shipwrecks, and submerged infrastructure

researcharxiv-cs-ro

Symmetry-Aware Feature Learning: A Polynomial Separation for Multi-Index Models

arXiv:2610.08420v1 Announce Type: new Abstract: We establish a polynomial sample complexity separation between symmetry-aware and symmetry-agnostic feature learning. We study growing-rank multi-index

TEMPEST: Temporal Embeddings for Scalable Driver Identification via Angular Margin Learning

arXiv:2610.06855v1 Announce Type: cross Abstract: Scalable driver identification requires embedding models that maintain discriminative performance as fleet size grows, yet existing triplet-loss formu

The Standardization Trap: Certifying Joint Label Processing in Tabular Foundation Models

arXiv:2610.08314v1 Announce Type: new Abstract: Linear regression and kernel smoothing offer tractable explanations of in-context learning: in both, the features determine the weight assigned to each

Towards One-for-All Foundation Model for Attributed Graph Clustering

arXiv:2610.07778v1 Announce Type: cross Abstract: Attributed graph clustering aims to discover node groups by jointly exploiting node attributes and graph topology, yet its unsupervised nature makes m

Trajectools Demo: Towards No-Code Solutions for Movement Data Analytics

arXiv:2610.06858v1 Announce Type: cross Abstract: This demo paper presents the conceptual foundations and the first steps towards implementation of a novel no-code solution for movement data analytics

Tree Navigation Without LLM Summaries: A Matched-Cost Study of Hierarchical Retrieval for Long-Document QA

arXiv:2610.06902v1 Announce Type: new Abstract: Retrieval-augmented generation grounds language models in external context, but for long documents flat top-k retrieval can cluster on a single region a

Trustworthy Method Comparison with AI Judges: Estimation and Design under Order, Batch, and Aggregation Effects

arXiv:2610.07755v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as judges for automated AI evaluation. A common practice is to randomize prompt sequences and avera

Turnslide: Scalable Multi-Turn Data Synthesis by Walking a Finite-State Machine

arXiv:2610.07070v1 Announce Type: new Abstract: Small language models are inexpensive to serve and can run on private infrastructure, but base models are often not good enough at multi-turn tool calli

Two-Sample Testing for Random Graphs without Vertex Correspondence

arXiv:2610.07503v1 Announce Type: cross Abstract: Two populations of graphs often have to be compared without any correspondence between their vertices, for instance when networks come from different

Two-Sample Testing via Generative Processes

arXiv:2610.08277v1 Announce Type: cross Abstract: Deciding whether two samples come from the same distribution is a classical problem in statistics, and generative transport offers a new way to approa

Two Vectors Replace In-Context Demos: Structured Task Adaptation via Embeddings

arXiv:2610.07572v1 Announce Type: new Abstract: In-context learning (ICL) adapts frozen large multimodal models (LMMs) to new tasks from a few demonstrations (demos), but re-encodes them at every quer

UltraDiff: Differentiable Ray Tracing in Ultrasound for Shape Optimization

arXiv:2610.07941v1 Announce Type: cross Abstract: Physically-based differentiable rendering enables gradient-based optimization of scene parameters by matching rendered images to measurements, but has

UniPose9D: Universal Category-Agnostic Object Pose Estimation

arXiv:2607.09985v2 Announce Type: replace Abstract: Object pose estimation is a fundamental problem in 3D vision. Although recent state-of-the-art approaches achieve strong performance, generalization

UniPro: Unified Multi-Mode Medical Image Segmentation from 2D Images to 3D Volumes via Propagation

arXiv:2610.06938v1 Announce Type: new Abstract: Medical image segmentation remains fragmented along two axes: segmentation paradigms and data dimensionality. Existing methods are typically developed s

UNREAL: Unifying Retrieval and Long-Context with a Single Model

arXiv:2610.08463v1 Announce Type: new Abstract: Long-context inference and Retrieval-Augmented Generation (RAG) handle evidence selection at vastly different scales, from a single long prompt to an en

Uploaded 5.6 billion TikTok videos metadata on Hugging Face, spanning from 2014 to October 2026 [P]

researchr-machinelearning

Dataset: https://huggingface.co/datasets/datasocial/tiktok-5.6B-videos If you want to explore the data without downloading billions of rows, you can query my ClickHouse database directly. It includes:

Valid for Free: Homophily-Gated Conformal Prediction for Training-Free Node Classification with Tabular Foundation Models

arXiv:2610.08564v1 Announce Type: new Abstract: Tabular foundation models (TFMs) can classify the nodes of a graph without training on it, by reading node and neighborhood features as table rows next

VALSE: Vertical Adaptive Layer Skipping for Efficient Inference in Large Language Models

arXiv:2610.07606v1 Announce Type: new Abstract: This paper establishes a theoretical framework for vertical adaptive layer skipping, proving three foundational results: (i) an Expected FLOPs formula (

Variational Physics-Informed Ansatz for Reconstructing Hidden Interaction Networks from Steady States

arXiv:2512.13708v2 Announce Type: replace Abstract: Inferring interaction structure from steady-state observations is a central inverse problem when transient trajectories are unavailable. Here we for

VietBinoculars: A Zero-Shot Approach for Detecting Vietnamese LLM-Generated Text

arXiv:2509.26189v2 Announce Type: replace Abstract: The rapid proliferation of Large Language Models has intensified the challenge of distinguishing LLM-generated text from human writing in non-Englis

View Matters: Keyframe-Guided Text-Driven 3D Gaussian Editing

arXiv:2610.08179v1 Announce Type: new Abstract: Text-driven 3D Gaussian editing commonly does not distinguish the editing reliability of rendered views, although different viewpoints provide supervisi

When Attention Does Not Explain the Peak: Temporal Reference vs. Forecast Output in Attention-Based Time-Series Forecasting

arXiv:2610.07080v1 Announce Type: new Abstract: Attention maps are often interpreted as evidence of what a forecasting model uses when making predictions. In our load-forecasting model, a CLS represen

When Can World Models Recover Physical Laws?

arXiv:2610.06877v1 Announce Type: cross Abstract: Accurate prediction does not establish that a world model has recovered a physical law: distinct dynamics can generate identical records under the sam

When Forgetting is not Catastrophic: On the Mechanics of Spurious Forgetting

arXiv:2610.08718v1 Announce Type: new Abstract: Knowledge that a language model appears to forget during finetuning often remains stored and can be recovered, a phenomenon called spurious forgetting.

When Old Facts Return: Re-Reads, Reverts, and the Limits of Temporal Memory

arXiv:2610.07715v1 Announce Type: cross Abstract: A memory system can retire an obsolete value and later restore it merely because the same old statement appears again. A re-read of an old source and

When to Rethink: Learning Multi-Perspective Self-Verification for Vision-Language Models

arXiv:2610.07018v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance in multimodal reasoning, yet they remain prone to generating plausible but incorrect answ

Where Do Test-Time Scaling and Training Fall Short in Individual Stance Prediction?

arXiv:2609.33155v2 Announce Type: replace Abstract: Test-time scaling and post-training have improved LLM performance in coding and mathematical reasoning, but their effectiveness for individual stanc

Which alloy composition,what process parameters? Inferring the recipe from optimized metallic microstructure and texture

arXiv:2610.08165v1 Announce Type: new Abstract: The mechanical properties of a metallic alloy are set by its microstructure and texture: the size and shape of its grains and the orientation of their c

Which and When to Admit: Gradient Admission for Data-Centric Small Language Model Finetuning

arXiv:2610.07553v1 Announce Type: cross Abstract: LoRA fine-tuning adapts small language models (SLMs) to heterogeneous instruction data within a low-rank update subspace, making it vulnerable to thre

X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness

arXiv:2610.08502v1 Announce Type: cross Abstract: Proactive power management systems reduce processor dynamic power through runtime power prediction and power-aware scheduling. Accurate, stable and lo

Zero-Shot Lombard Speech Synthesis with Controllable Style Embeddings

arXiv:2601.12966v2 Announce Type: replace-cross Abstract: The Lombard effect plays a key role in natural communication, particularly in noisy environments or when addressing hearing-impaired listeners

A Biomimetic Gaze Control to Restore Head-Neck Movements

arXiv:2610.04022v1 Announce Type: new Abstract: Powered neck exoskeletons are developed to restore head-neck motions for those with neck muscle weakness. Current methods using hand-held input devices

researcharxiv-cs-ro

A Contrast-Source Inversion Scheme Based on Stochastic Optimization and Plug-and-Play Regularization

arXiv:2610.05130v1 Announce Type: cross Abstract: An electromagnetic inversion scheme that integrates stochastic optimization (STO) and plug-and-play (PNP) regularization into contrast-source inversio

A General Pipeline for Dense Illuminant Estimation via Physically Based Synthetic Data

arXiv:2610.06508v1 Announce Type: new Abstract: Illuminant estimation is a fundamental problem in computational photography, as it enables the correction of color shifts induced by varying lighting co

A Graph-Based Inspection and Intervention Tool for Assessing Mechanistic Learning in PINNs

arXiv:2610.04939v1 Announce Type: new Abstract: We ask whether physically meaningful correspondences discovered inside a trained scientific model remain meaningful outside the conditions under which t

A Hand-Checkable Proof That Two Hidden ReLU Layers Compute the Maximum of Six Numbers

arXiv:2610.04256v1 Announce Type: new Abstract: Exactly computing the maximum function is a standard test case for studying depth in ReLU networks. Two hidden layers are known to suffice for up to twe

A multi-stage probabilistic framework to estimate gas-fired generator performance during extreme winter weather

arXiv:2610.04368v1 Announce Type: new Abstract: Extreme winter weather has repeatedly disrupted gas-fired power generation in the United States, yet the plant-level data needed to systematically quant

A Multimodal Sequence-to-Sequence Model for Cross-Subject Prediction of Brain Responses to Naturalistic Stimuli

arXiv:2507.18104v3 Announce Type: replace Abstract: Brain encoding models predict time-resolved neural activity from computational representations of ongoing experience, providing a principled framewo

A Physics-Guided Transformer Framework for Electromigration Analysis in Multi-Segment Interconnects

arXiv:2610.06464v1 Announce Type: new Abstract: As technology scales to smaller nodes, increasing current densities make electromigration (EM) one of the dominant reliability challenges in on-chip int

A Response Theory Probe for Learned Stochastic AI Simulators, Tested on Lorenz-63

arXiv:2610.06798v1 Announce Type: cross Abstract: Machine-learning emulators of chaotic and stochastic systems are usually validated on forecast skill and long-run statistics. Neither certifies that a

A Solvable Model of Adaptive Learning Rate Rescaling: Acceleration, Stability & Scaling

arXiv:2610.06701v1 Announce Type: cross Abstract: A recurring design principle in modern optimizers is to decouple update magnitude from the raw gradient norm, yet its consequences for learning-curve

A Strong Baseline for Evaluating Vision Encoders in Multimodal Large Language Models

arXiv:2610.05413v1 Announce Type: new Abstract: Evaluating vision encoders requires metrics that reliably predict their downstream performance in multimodal large language models (MLLMs). Although rec

A Testable Theory of Atomic Features

arXiv:2610.05794v1 Announce Type: cross Abstract: We develop and test a theory of language model representations in which there exist atomic features. Our main theoretical insight is that in such a mo

A Three-Dimensional Reverse-Projection Method for Sparse Point Cloud Completion and Its Application to High-Speed Train Nose Reconstruction

arXiv:2610.05758v1 Announce Type: new Abstract: Holes in LiDAR scans of environments with glass windows remain an unresolved problem in three-dimensional reconstruction. This study presents a pipeline

A Unifying Perspective on Descent Directions for Constrained Minimization and Switching Criteria

arXiv:2006.08426v5 Announce Type: replace-cross Abstract: Descent directions are fundamental to first-order methods for constrained convex optimization. In this work, we provide a unified perspective