Knowledge catalogue
arXiv:2609.22081v1 Announce Type: new Abstract: Occupational accident narratives contain valuable information about work situations, unfavourable conditions, accident events, and their consequences. A
arXiv:2609.21347v1 Announce Type: new Abstract: Recent progress in 3D Gaussian Splatting (3DGS) has enabled dense visual SLAM with pinhole cameras, yet most pipelines are not designed for panoramic im
arXiv:2609.20839v1 Announce Type: new Abstract: Phoneme-centric visual speech recognition reconstructs sentences from intermediate phoneme predictions, making overall recognition performance highly de
arXiv:2609.21113v1 Announce Type: new Abstract: Fine-tuning has emerged as a widely adopted approach for adapting LLMs to a variety of downstream tasks. However, how it reshapes their internal mechani
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
arXiv:2609.21888v1 Announce Type: cross Abstract: Detecting pretraining data in large language models is challenging because high likelihood can reflect either training exposure or strong generalizati
arXiv:2609.21628v1 Announce Type: new Abstract: Automatic tooth segmentation and FDI numbering on panoramic radiographs underpins computer-assisted dental diagnosis, yet which factors govern performan
arXiv:2609.22008v1 Announce Type: cross Abstract: Vision-language models (VLMs) rely on storing and transferring appropriate information across their sub-components. Verifying that the VLMs exhibit de
arXiv:2609.21698v1 Announce Type: new Abstract: Deep learning segmentation of renal tumors requires large annotated datasets, yet clinical deployments typically offer only a handful of tumor-positive
arXiv:2609.21675v1 Announce Type: new Abstract: Despite the remarkable progress in Multimodal Large Language Models (MLLMs), prevailing Chain-of-Thought (CoT) paradigms remain confined to the natural-
arXiv:2412.07151v1 Announce Type: cross Abstract: Distributed model training needs to be adapted to challenges such as the straggler effect and Byzantine attacks. When coordinating the training proces
arXiv:2609.21099v1 Announce Type: new Abstract: Coaxial rotor drones have generated considerable interest because of energy efficiency and small size, but they are afflicted with inherent underactuati
arXiv:2609.21100v1 Announce Type: new Abstract: Learning in robotic games is constrained not only by strategic information but also by what the body can still execute. We study this coupling in a hier
arXiv:2510.13046v3 Announce Type: replace Abstract: State space models offer linear-time sequence modeling and are a promising backbone for multi-label 12-lead ECG classification, but the design choic
arXiv:2609.21755v1 Announce Type: new Abstract: Emergency department (ED) decision-making relies on heterogeneous clinical information, including patient history, vital signs, laboratory results, and
arXiv:2609.21268v1 Announce Type: new Abstract: Text-guided video editing modifies target content while preserving the appearance and temporal coherence of unedited regions. Training-based approaches
arXiv:2609.21457v1 Announce Type: new Abstract: Deep neural architectures are widely used for signal processing in automated pain assessment systems. However, architecture design has remained largely
arXiv:2602.18071v2 Announce Type: replace Abstract: Humans rearrange objects in cluttered environments using egocentric perception, actively moving to keep task-relevant spatial cues in view. Mobile r
arXiv:2609.21941v1 Announce Type: cross Abstract: The importance of deep neural networks (DNNs) is widely recognized, and the parameters obtained through training are regarded as valuable assets. Rece
arXiv:2609.20849v1 Announce Type: new Abstract: Large Audio Language Models (LALMs) perform well on complex question answering but often show a reasoning gap, where explicit Chain-of-Thought (CoT) red
arXiv:2601.06848v2 Announce Type: replace Abstract: Multimodal aspect-based sentiment analysis (MABSA) aims to identify aspect-level sentiments by jointly modeling textual and visual information, whic
arXiv:2609.21629v1 Announce Type: new Abstract: Multi-Channel imaging (MCI) data differs fundamentally from natural images, as each channel records a semantically distinct signal rather than a colour
arXiv:2609.20897v1 Announce Type: cross Abstract: We study a minimal classification problem: Given independent labeled observations Xsim P and Zsim Q from two unknown distributions P,Q, and given an i
arXiv:2609.21306v1 Announce Type: new Abstract: A common requirement across organizations is to have a tool that can identify file types based on their contents, particularly in the cybersecurity doma
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
Finally, a company brain that actually works! Codos starts with the people doing the work. It interviews employees to find which tasks can be automated, then deploys the automations and keeps learning
arXiv:2609.21497v1 Announce Type: new Abstract: Effective physical interaction control in robotic manipulation requires not only kinematically feasible motion but also sufficient force-interaction cap
arXiv:2609.21012v1 Announce Type: new Abstract: Artistic style classification is usually studied on complete artworks, where models can exploit global composition, spatial organisation, and iconograph
arXiv:2609.21667v1 Announce Type: cross Abstract: Software is a first-class scientific object, yet validated links between source code and the scholarly record remain largely absent from the Linked Op
arXiv:2609.20838v1 Announce Type: new Abstract: In this study, we examine how modern LLMs generate and detect fake news under controlled settings across four manipulation scenarios. These are open-end
arXiv:2609.21349v1 Announce Type: cross Abstract: Large language models have shown strong potential as role-playing agents for real individuals, yet faithful impersonating remains challenging. Existin
arXiv:2609.21543v1 Announce Type: new Abstract: Does a general vision--language model acquire specialized OCR ability by developing a new reading circuit or by reusing an existing mechanism? We addres
arXiv:2609.20991v1 Announce Type: new Abstract: Physiological emotion recognition using wearable sensors has important applications in mental health monitoring, affective computing, and human-computer
arXiv:2609.20968v1 Announce Type: new Abstract: In non-stationary online learning, dynamic regret has attracted increasing attention as a measure of how well an online learner performs against a time-
arXiv:2609.21117v1 Announce Type: cross Abstract: AI productivity is often measured by task completion time, economic value, or improvements in outcome quality. However, these measures usually treat c
arXiv:2609.21243v1 Announce Type: cross Abstract: Barren plateau diagnostics characterize whether gradient signal remains available for training, but surviving signal need not translate into successfu
arXiv:2609.21251v1 Announce Type: new Abstract: Gradient-guided diffusion samplers provide flexible priors for inverse problems and conditional generation, but strong guidance can move the sampling tr
arXiv:2609.21576v1 Announce Type: new Abstract: Generating natural co-speech gestures from streaming speech is essential for embodied conversational agents, where motion must be produced while a user
arXiv:2609.22039v1 Announce Type: cross Abstract: We need studies on conversational AI (CAI) at scale to understand human behavior and shape CAI design. However, fragmented reporting of systems and st
arXiv:2609.21227v1 Announce Type: cross Abstract: Factual hallucination is commonly defined by incorrect factual outputs. We study a paraphrase-induced hallucination setting, where a model answers a f
arXiv:2609.21207v1 Announce Type: new Abstract: Procedural anomaly detection in bimanual assembly requires judging each hand action against the execution so far. A corrective action may look unusual i
arXiv:2609.20825v1 Announce Type: new Abstract: Clinical predictive models often rely on structured Electronic Health Record data, such as time-series and procedure codes. While recent approaches have
arXiv:2309.13476v3 Announce Type: replace Abstract: Depression is a common mental disorder. Automatic depression detection tools using speech, enabled by machine learning, help early screening of depr
arXiv:2609.21277v1 Announce Type: new Abstract: How many human judgments does a panel of language models represent? The answer depends on what is matched. We audit categorical judge panels against emp
arXiv:2609.21183v1 Announce Type: cross Abstract: Audio large language models (AudioLLMs) operate reactively, responding only when queried. We introduce proactive audio assistance, where an AudioLLM m
arXiv:2609.20975v1 Announce Type: new Abstract: Affordable dust monitoring remains a pressing need for the cattle feedlot industry, yet camera-based PM estimation, despite its growing body of research
arXiv:2609.21181v1 Announce Type: new Abstract: The Abstraction and Reasoning Corpus and related benchmarks evaluate whether AI models can solve novel reasoning tasks, but often leave unclear whether
arXiv:2609.21932v1 Announce Type: new Abstract: Joint remaining useful life (RUL) prediction and capacity estimation require representations of both gradual degradation and recent battery behavior. Th
arXiv:2609.21926v1 Announce Type: new Abstract: Many machine learning systems try to explain complex data - like images or financial time series - in terms of hidden, independent factors that generate
arXiv:2609.21126v1 Announce Type: new Abstract: We propose a decoupled, layerwise method for structurally sparsifying the fully connected layers of pretrained neural networks. Rather than penalizing a
arXiv:2609.21962v1 Announce Type: new Abstract: Electrocardiograms (ECGs) carry subject-specific patterns enabling reliable individual discrimination, forming the basis of ECG biometrics. Beyond authe
arXiv:2609.21319v1 Announce Type: new Abstract: Physical control tasks in the natural world, such as driving or object manipulation, frequently exhibit dramatic variations in sensory and compute compl
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
arXiv:2609.21801v1 Announce Type: new Abstract: We study how far a simple statistical pipeline can go on univariate time series anomaly detection under a strict selection protocol. The method extracts
arXiv:2609.21894v1 Announce Type: new Abstract: We introduce an iterative framework that automates the extraction of interpretable, schema-bound categorical features from unstructured text for tabular
arXiv:2609.21492v1 Announce Type: new Abstract: Chain-of-Thought (CoT) reasoning has been shown to improve the performance of large language models (LLMs), yet existing optimization methods largely re
arXiv:2609.21275v1 Announce Type: new Abstract: We introduce Learned Optimal Inverse Kinematics (LOInK), a method to generate approximately optimal solutions to an inverse kinematics problem. When tra
arXiv:2609.21818v1 Announce Type: new Abstract: The performance improvement of high-power flat BLDC motors has accelerated the development of dynamic robots. However, many commercially available servo
arXiv:2609.21018v1 Announce Type: new Abstract: Recent visual document retrieval (VDR) systems such as ColPali use multi-vector page embeddings, in which patch-level vectors enable fine-grained eviden
arXiv:2609.21396v1 Announce Type: new Abstract: Underwater robot development is often hindered by the complexities of waterproofing and wiring, which significantly delay the rapid prototyping process.