Search: “research”

MedHal: a Synthetic Dataset for Medical Hallucination Detection

arXiv:2504.08596v3 Announce Type: replace-cross Abstract: Hallucination, the generation of non factual content by AI systems, poses serious risks in medical contexts, where errors can directly affect

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Moving Horizon Estimation for Quadrotors: An L_1 Adaptive Optimizer Approach

DGX agent

arXiv:2609.30777v1 Announce Type: new Abstract: Moving Horizon Estimation (MHE) is a state estimation method based on finite-horizon optimization that can offer higher accuracy at the cost of increase

researcharxiv-cs-ro

28 Sept 2026

Multi-Objective Human-in-the-Loop Bayesian Optimization of a Lower-Limb Exoskeleton

arXiv:2609.30695v1 Announce Type: new Abstract: Human-in-the-loop optimization (HILO) is a common approach for optimizing the control of assistive devices to account for the wearer's unique biomechani

Testing the Utility of Using Large Language Models to Create Personalized Networks From Therapy Session Transcripts: A Proof of Concept Study

arXiv:2512.05836v2 Announce Type: replace Abstract: Recent advances in psychotherapy have focused on treatment personalization, such as by selecting treatment modules based on individual networks. How

Toward AI-Augmented Cooperative Engineering Workflows: Requirements and Architecture the European Rover Challenge

arXiv:2609.31136v1 Announce Type: new Abstract: The growing availability of Artificial Intelligence (AI) tools creates new opportunities to support engineering design processes, yet their current use

UniPrefill: Universal Long-Context Prefill Acceleration via Block-wise Dynamic Sparsification

arXiv:2605.06221v2 Announce Type: replace Abstract: As large language models (LLMs) continue to advance rapidly, they are becoming increasingly capable while simultaneously demanding ever-longer conte

Unsupervised Methods for Video Quality Improvement: A Survey of Restoration and Enhancement Techniques

arXiv:2507.08375v2 Announce Type: replace Abstract: Video restoration and enhancement are critical not only for improving visual quality, but also as essential pre-processing steps to boost the perfor

Modeling Load-, Velocity-, and Temperature-Dependent Transmission Errors of Cycloidal Drives for Industrial Robots Using Fourier Series

arXiv:2609.29112v1 Announce Type: new Abstract: Industrial robots are rarely used for machining tasks due to their limited path accuracy. This accuracy is mainly limited by inaccuracies in the drive t

25 Sept 2026

The Entropy Triangle Method (ETM): A novel framework for the prevention of cardiac arrhythmia with a review of more than 10,000 patients

arXiv:2609.29187v1 Announce Type: new Abstract: One of the most important problems in medicine is to facilitate prediction. In this study, we propose entropy triangle method, a novel framework for pre

25 Sept 2026

Digital diglossia: Arabic between X and Facebook

arXiv:2609.28352v1 Announce Type: new Abstract: This study highlights the distribution of Standard Arabic (SA; H(igh) variety) and Colloquial Arabic (CA; L(ow) variety) across X and Facebook. 16754 pu

EduBehaviors: Assertion-based Schemas for Auditable Coding of Educational Dialogues

arXiv:2609.27043v1 Announce Type: new Abstract: Large language models have allowed the rapid deployment of pedagogical annotations corresponding to constructs of interest, allowing a natural language

Enhancing Multiclass Malware Classification in Resource-Constrained Environments

arXiv:2609.27950v1 Announce Type: cross Abstract: The emergence of multi-class malware attacks such as ransomware, spyware, trojans, etc., presents an increasing and serious threat to cybersecurity, p

Evaluating ADC-only deep learning pipelines for breast cancer detection and segmentation using standalone diffusion-weighted MRI

arXiv:2609.27815v1 Announce Type: cross Abstract: Dynamic contrast-enhanced (DCE) imaging is the gold standard technique for the detection and characterization of breast cancer using magnetic resonanc

Safety

Propose, Don't Judge: An Anytime-Valid Referee for LLM Agents That Mine Investment Factors

arXiv:2609.27051v1 Announce Type: new Abstract: Language-model agents now run the whole of quantitative factor research: they propose investment factors, backtest them, select the survivors and retire

safetyarxiv-cs-ai

Radiomics and artificial Intelligence for thyroid cancer diagnosis: Concepts, challenges, and solutions

arXiv:2404.07239v2 Announce Type: replace-cross Abstract: Thyroid cancer is an increasing global health concern that requires advanced diagnostic methods. The application of AI and radiomics to thyroi

StudentBench: AI and human tutoring yield equivalent GRE learning gains

arXiv:2609.28470v1 Announce Type: new Abstract: Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advanci

ThaiTrees: Thai Syntactic Dependency Trees Across Domains

arXiv:2609.27558v1 Announce Type: new Abstract: Studying syntactic patterns in naturally occurring language requires a large parsed corpus, but manual annotation is costly and difficult to scale. Thai

The Gaussian Is Enough: Flow-Matching Priors Do Not Help When Fine-Tuning Large Behavior Models

arXiv:2609.27070v1 Announce Type: cross Abstract: Modern robot imitation learning increasingly relies on generative policies based on diffusion or flow-matching models, which generate actions by trans

TNLearn: An Open Source Python Package for Task-based Neurons

arXiv:2609.27564v1 Announce Type: cross Abstract: The brain does not rely on a single type of neuron to perform all kinds of tasks; instead, it designs different neurons for different tasks. The conce

A retrospective analysis on the use of LLMs to study infant syntax learning

arXiv:2609.26539v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly been used to investigate how children acquire syntax at an early stage of development. This is notably th

A Survey on the Linear Representation Hypothesis

arXiv:2609.22695v1 Announce Type: new Abstract: The term 'linear representation hypothesis' (LRH) has appeared across diverse subfields of artificial intelligence, neuroscience, and cognitive science.

AgriGen: Large-Scale Scene Generation Framework for Photorealistic Agricultural Robotics Simulation

arXiv:2609.25725v1 Announce Type: new Abstract: Agricultural robotics is advancing rapidly, yet progress remains constrained by limited field access, lack of control over field conditions, geographic

Model Releases

BackTrend: Evaluating Scientific Weak-Signal Prediction via Backward Reconstruction

model-releasesarxiv-cs-ai

arXiv:2609.24921v1 Announce Type: new Abstract: Scientific weak signals are early, low-visibility research directions that later become central to mature scientific topics, yet existing resources such

Calibrated Confidence Expression for Radiology Report Generation

arXiv:2603.29492v2 Announce Type: replace Abstract: Safe deployment of Large Vision-Language Models (LVLMs) in radiology report generation requires not only accurate predictions but also clinically in

Designing and Analysing Argument Mining Pipelines: Towards a Comprehensive Assessment

arXiv:2609.26338v1 Announce Type: new Abstract: Argument Mining (AM) transforms natural language into its underlying argument structures. This transformation is typically realized through a sequence o

FleXray: Universal Clinical X-ray Segmentation

arXiv:2609.26756v2 Announce Type: new Abstract: X-ray is medicine's most widely used imaging modality, yet remains among its least quantitative. Unlike volumetric modalities like CT or MRI, X-ray coll

Low-Rank Attention Residuals

arXiv:2607.09694v2 Announce Type: replace-cross Abstract: Attention Residuals (AttnRes) replace the fixed residual sum with depth-wise attention over previous sub-layer outputs in Large Language Model

PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics

arXiv:2609.25438v1 Announce Type: new Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-

Polyak-Type Extragradient Methods for Monotone Root-Finding Problems

arXiv:2609.26581v1 Announce Type: cross Abstract: We study Polyak-type step-size selection for extragradient methods for solving deterministic and stochastic monotone root-finding problems. We show th

Assessing Adversarial Robustness of Latent Reasoning Models

arXiv:2609.22228v1 Announce Type: new Abstract: Large language models increasingly rely on long chain-of-thought (CoT) trajectories for complex reasoning, but autoregressive generation brings substant

Beyond the Survey: A Systematic Empirical Study of Detection and Association in Visual MOT

arXiv:2609.22291v1 Announce Type: new Abstract: This paper presents a comprehensive experimental evaluation and detailed analysis of state-of-the-art multi-object tracking algorithms, with an emphasis

CTSpinoPelvic1K: spine, pelvis, ribs and femora in one coordinate frame, annotated for lumbosacral transitional anatomy

arXiv:2609.22760v1 Announce Type: cross Abstract: Purpose: A vertebra at the lumbosacral junction is named by counting caudally from C2 on whole-spine imaging, but a lumbar case is planned on lumbar-o

End-to-end Jordanian dialect speech-to-text self-supervised learning framework

arXiv:2609.24410v1 Announce Type: new Abstract: Speech-to-text engines are extremely needed nowadays for different applications, representing an essential enabler in human-robot interaction. Still, so

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

Leveraging Industrial Foundation Models at the Edge of Particle Physics Detectors via Distillation Learning and Hardware Co-design

arXiv:2609.23385v1 Announce Type: cross Abstract: Data acquisition (DAQ) systems at future particle physics experiments stand to benefit from the extremes of AI/ML development: large-scale foundation

Model Releases

SCoR: A Hierarchical Framework for Forecasting Relations Between Scientific Concepts

model-releasesarxiv-cs-cl

arXiv:2609.22174v1 Announce Type: new Abstract: Anticipating emerging research directions is a critical goal of AI-assisted science. Existing methods mainly predict which concepts will co-occur in fut

TEMPER: Temporal Encoder-Masked Probabilistic Ensemble Regressor for Time-Series Forecasting

arXiv:2609.23701v1 Announce Type: cross Abstract: Probabilistic forecasting requires accurate central predictions and calibrated uncertainty estimates. This paper presents TEMPER, the Temporal Encoder

Deep Learning-Enhanced Real-Time Wi-Fi Sensing Through Single Transceiver Pair

arXiv:2511.02845v3 Announce Type: replace-cross Abstract: The advancement of next-generation Wi-Fi technology heavily relies on sensing capabilities, which play a pivotal role in enabling sophisticate

Field Tracking of Insects Using a Stereoscopic Event-Based Camera Setup

arXiv:2609.21354v1 Announce Type: new Abstract: High-speed tracking of small, fast-moving organisms in their natural environments is important to better understand their behavior and ecology. Traditio

Listen Before You Speak: Response Planning from Listener Facial Reactions for Conversational Speech Generation

arXiv:2609.21683v1 Announce Type: new Abstract: Conversational speech depends on dialogue context and the listener's immediately preceding behavior. We propose ReACT-TTS, a two-stage framework that us

Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses

arXiv:2402.04013v3 Announce Type: replace Abstract: Deep Neural Networks (DNNs) have revolutionized various domains with their exceptional performance across numerous applications. However, Model Inve

Triply-Scalable Equivariant Gaussian Process Modeling

arXiv:2609.21085v1 Announce Type: cross Abstract: Gaussian processes (GPs) provide principled probabilistic predictions while encoding prior knowledge, including equivariances. Yet, their use in large

Understanding Engagement and Intrusiveness in Assistive Human-Robot Interaction Using Individual Traits

arXiv:2609.21744v1 Announce Type: new Abstract: Robot assistance is particularly crucial in unfamiliar tasks, where users must understand task requirements while coordinating with the robot. Previous

A Morphing Aerial Robot With Thruster-Integrated Flexible Continuum Links for Shape Adaptive Aerial Manipulation

arXiv:2609.19328v1 Announce Type: new Abstract: In recent years, aerial manipulation has attracted increasing attention as a key to expand the application of aerial robots. In this work, we focus on t

Building a Neural Network from Scratch: Implementation, Evaluation, and Optimization

arXiv:2607.16682v2 Announce Type: replace-cross Abstract: The widespread adoption of high-level deep learning libraries, while accelerating model development, has increasingly abstracted away the inte

Finding Common Ground: Graded Communal Knowledge in Bluesky Starter Packs

arXiv:2609.19549v1 Announce Type: cross Abstract: Communication is made possible by common ground---the unspoken knowledge that people share and presuppose of one another, whether that be online or of

Generalization through Lexical Abstraction in Transformer Models: The Case of Functional Words

arXiv:2609.19887v1 Announce Type: new Abstract: Pronouns, adverbs and other functional words (such as they, her, somewhere, there) are often used in language to replace concrete nouns or phrases, when

Learn2Drive: A neural network-based framework for socially compliant automated vehicle control

arXiv:2510.21736v2 Announce Type: replace-cross Abstract: This study introduces a novel control framework for adaptive cruise control (ACC) in automated driving, leveraging neural networks and physics