Knowledge catalogue
arXiv:2505.12192v2 Announce Type: replace Abstract: Early detection of PD remains particularly challenging in resource-constrained settings, where voice-based analysis has emerged as a promising non-i
arXiv:2609.16069v1 Announce Type: cross Abstract: Synthetic tabular data can match real data distributions while still violating the semantic constraints that govern valid tabular rows. This reveals a
arXiv:2609.16040v1 Announce Type: new Abstract: Bilateral control-based imitation learning captures both position and force information, making it well suited to contact-rich manipulation. However, ex
arXiv:2609.16338v1 Announce Type: new Abstract: Ternary Large Language Models (LLM) store every weight as one of three symbols {-1,0,+1}, so the cost of a ternary model is conventionally referenced to
arXiv:2609.16742v1 Announce Type: cross Abstract: Convolutional Neural Networks (CNNs) are increasingly deployed in safety-critical edge applications, where soft errors can silently corrupt inference
Connected data gives artificial intelligence agents the context required to handle critical business work. Enterprises are beginning to assign AI more consequential tasks, but fragmented records and u
arXiv:2609.16322v1 Announce Type: new Abstract: Surrogate credibility for fluid-structure interac- tion (FSI) requires distinguishing transfer across independent anatomies from interpolation within an
arXiv:2609.16635v1 Announce Type: new Abstract: Computer-use agents increasingly operate browsers, software, and desktop applications via CLI or API portals, but graphical user interface (GUI) still p
arXiv:2609.16926v1 Announce Type: new Abstract: Phenotyping an agricultural crop is crucial for studying its entire life cycle, as it provides vital insights to improve yield and, ultimately, food pro
arXiv:2609.17134v1 Announce Type: new Abstract: Neuromorphic vision systems operate under strict constraints on bandwidth, memory, and energy, particularly at the edge, motivating early mechanisms for
Enterprise artificial intelligence services startup Hang Ten Systems Inc. today announced it has raised 53 million in a second seed round, less than three months after announcing its first. Hang Ten p
arXiv:2609.17111v1 Announce Type: cross Abstract: Modelling with mathematical formalisms like logical formulas, mathematical equations, or regular expressions is an important yet challenging task for
arXiv:2609.16465v1 Announce Type: cross Abstract: We present an automated pipeline that converts hair-card models into high-quality strand-based hairstyles. Given a collection of textured triangular o
arXiv:2609.16222v1 Announce Type: new Abstract: Stopgrads are widely used in training machine learning models, but stopgrads can alter the gradient, stationary points and convergence guarantees of the
arXiv:2609.17376v1 Announce Type: cross Abstract: Large language models (LLMs) trained on next-token prediction exhibit remarkable in-context learning (ICL) abilities, yet the representations that sup
arXiv:2603.08283v2 Announce Type: replace Abstract: Complex constraints often make real-world optimization computationally prohibitive at the scale and speed required for operational decision-making.
arXiv:2609.16730v1 Announce Type: new Abstract: Conversational memory changes during use, so endpoint question answering alone cannot establish how a persistent state accumulates, ages, or incorporate
arXiv:2609.17524v1 Announce Type: new Abstract: World-action models (WAMs) jointly model future observations and actions, typically predicting the future as RGB images. Other visual modalities such as
arXiv:2609.16347v1 Announce Type: new Abstract: Sea-ice type prediction is important for climate monitoring, maritime navigation, and decision-making in polar regions. The main source of label data fo
arXiv:2512.15708v2 Announce Type: replace Abstract: Foundation models are vital tools in various Computer Vision applications. They take as input a single RGB image and output a deep feature represent
arXiv:2609.16010v1 Announce Type: new Abstract: The complexity of legal language and limited accessibility to legal information pose significant challenges to justice delivery in Nepal. Traditional le
arXiv:2609.15999v1 Announce Type: new Abstract: Accessing legal information in Nepal is difficult due to complex terminology, limited resources, and misinformation. We introduce an AI-powered legal as
arXiv:2609.16996v1 Announce Type: new Abstract: Many publications on robotic systems in healthcare describe early-stage work on low technology readiness levels. This paper describes how a mobile servi
arXiv:2609.16063v1 Announce Type: new Abstract: We study signed, weighted affine p-adic residual objectives as native encodings of finite-domain constraints. For primes that separate the finite alphab
arXiv:2609.17422v1 Announce Type: new Abstract: Audio-driven digital human generation plays an important role in virtual communication, immersive interaction, and media production. With the developmen
arXiv:2609.16256v1 Announce Type: new Abstract: Continuum robots enable smooth shape morphing and safe interaction in confined environments. However, most existing systems are task-specific and depend
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What’s at stake in AI’s trillion-dollar gamble When Jessica Wa
arXiv:2609.16856v1 Announce Type: cross Abstract: English Wikipedia is one of the largest examples of collective intelligence on the Web, sustained not only by article production but also by volunteer
the risks WERE foreseeable; i foresaw them. repeatedly, focusing specifically on the risks of LLMs and cybersecurity. happy to provide receipts on request. I’m not a lawyer, but Sam Altman and Dario A
arXiv:2609.16993v1 Announce Type: cross Abstract: Large Language Models are now common in student assessment, but we know little about how student demographics affect their use. Sometimes, considering
The state of public AI benchmarking is dire and is undermining our ability to understand how good AI is now. Most famous measures are maxed out, and, as this paper shows, the non-saturated benchmarks
This is an excellent demo of an AI model designed to rapidly classify information according to decision rules, much faster and cheaper than an LLM. It is not an LLM itself and cannot output text or co
arXiv:2609.16796v1 Announce Type: cross Abstract: Time-warping estimation is a fundamental problem in signal processing with applications in bioacoustics, radar, and biomedical analysis. This paper in
arXiv:2609.16644v1 Announce Type: new Abstract: World Action Models (WAMs) offer a promising approach to general-purpose robot manipulation by jointly modeling visual dynamics and actions. However, mo
arXiv:2609.16437v1 Announce Type: new Abstract: Collecting high-quality robot data for contact-rich manipulation tasks is essential for enabling robots to acquire real-world skills. However, existing
arXiv:2609.15427v1 Announce Type: cross Abstract: Using food package images to monitor sodium and salt content against South Africa's R214 sodium limits is challenging when screening decisions require
arXiv:2609.14145v1 Announce Type: cross Abstract: Kinship verification is a task involving determining whether two individuals share a first-order kin relation. To tackle this task, we propose CONVTRA
arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and
arXiv:2603.11667v3 Announce Type: replace Abstract: This paper examines how value is constructed and negotiated in today's increasingly automated language and translation industry. Drawing on intervie
arXiv:2609.15232v1 Announce Type: new Abstract: The introduction of human-robot collaboration (HRC) in industrial assembly operations is revolutionizing the manufacturing landscape. In this evolving e
arXiv:2609.14572v1 Announce Type: cross Abstract: Teaching abstract theoretical computer science (TCS) concepts such as algorithm analysis and complexity theory is challenging because students must ha
arXiv:2609.15702v1 Announce Type: new Abstract: Pretrained score-based diffusion models provide strong unconditional priors, yet enforcing measurement or physics consistency in inverse problems is oft
arXiv:2609.13815v1 Announce Type: new Abstract: Text-centric Visual Question Answering (VQA) requires reading and reasoning over text embedded in images, a task made substantially harder when images s
arXiv:2504.01157v1 Announce Type: cross Abstract: Knowledge-intensive analytical applications retrieve context from both structured tabular data and unstructured, text-free documents for effective dec
Good Start Labs experiments show that AI training with gameplay can lead to transferable skills: a version trained on a railroad simulation outperformed peers in financial research. Inspired by Twitch
arXiv:2411.09073v4 Announce Type: replace-cross Abstract: Large language models (LLMs) show strong performance across many tasks but remain weak at understanding code-mixed (CM) language. Despite this
arXiv:2609.14439v1 Announce Type: new Abstract: Blind image inpainting, aiming to recover contaminated images in the case of unknown masks, is a challenging task. Motivated by the perspective of human
arXiv:2609.13942v1 Announce Type: cross Abstract: The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation (MT) based on Large Language Models (LLMs)
arXiv:2609.13712v1 Announce Type: new Abstract: Many real-world scenarios can be represented using graph-structured data. However, traditional GNNs that transmit messages based on first-order neighbor
arXiv:2609.15570v1 Announce Type: new Abstract: World Action Models (WAMs) use video generation models to predict future visual dynamics for robotic manipulation, but iterative denoising introduces ad
arXiv:2609.13990v1 Announce Type: cross Abstract: Diffusion-based generative models (DMs) have found applications in control problems, and in particular robotics, where the DMs enable exploration of p
arXiv:2506.06977v4 Announce Type: replace-cross Abstract: Domain generalization has become a critical challenge in predictive healthcare, where different patient groups exhibit shifting data distribut
arXiv:2609.15861v1 Announce Type: new Abstract: Uncrewed Aerial Manipulators (UAMs) extend the capabilities of Uncrewed Aerial Vehicles (UAVs) from perception to physical interaction. Among various ae
arXiv:2609.14408v1 Announce Type: new Abstract: We present an automated pipeline that converts NCERT textbooks into interactive video explanations that respond directly to user queries. A user uploads
arXiv:2609.14498v1 Announce Type: cross Abstract: Sensor-based human activity recognition (HAR) is fundamental to ubiquitous and wearable computing, yet existing foundation models are largely designed
arXiv:2512.08661v2 Announce Type: replace Abstract: This paper addresses the problem of trajectory planning for information gathering with a dynamic and resolution-varying sensor footprint. Ergodic pl
arXiv:2607.15080v2 Announce Type: replace Abstract: This article explores the application of covariate balance diagnostics for detecting the presence of hidden confounding/model miss-specification in
arXiv:2609.13854v1 Announce Type: new Abstract: Facial emotion recognition (FER) in real-world environments remains challenging due to unconstrained imaging conditions, including multiple faces, occlu
arXiv:2509.24988v2 Announce Type: replace-cross Abstract: Generating accurate and calibrated confidence estimates is critical for deploying LLMs in high-stakes or user-facing applications, and remains
arXiv:2609.13812v1 Announce Type: new Abstract: We present GeomVLA, a Vision-Language-Action (VLA) model that unifies perception, latent scene motion prediction, and action generation within a shared