Knowledge catalogue
arXiv:2609.16567v1 Announce Type: new Abstract: Modern Visual Question Answering (VQA) models often exploit spurious correlations in training data, leading to poor out-of-distribution (OOD) generaliza
arXiv:2609.16686v1 Announce Type: cross Abstract: Estimating deformable object states remains a fundamental challenge in robotics and simulation. We propose a novel factor graph-based framework for pr
arXiv:2609.16062v1 Announce Type: cross Abstract: The studying of opinion dynamics and its propagation within social networks is crucial for addressing a wide range of challenges, including political
arXiv:2609.16321v1 Announce Type: cross Abstract: Existing fairness analysis tools predominantly operate as post-training evaluation frameworks, requiring practitioners to complete the full model deve
arXiv:2609.17391v1 Announce Type: new Abstract: Model serving is one of the largest cost drivers in production recommender systems. Maximizing its throughput requires navigating a deeply layered hiera
arXiv:2609.16378v1 Announce Type: cross Abstract: Digital twins provide a scalable and cost-effective complement to real-world testing for validating autonomous-driving and advanced driver-assistance
arXiv:2609.16163v1 Announce Type: new Abstract: The sharp increase in mass shootings underscores an urgent need for systems that guide victims to safety in real time. An effective evacuation system mu
arXiv:2609.16964v1 Announce Type: new Abstract: Rapid extraction of structured information from social media is important for humanitarian response, yet existing disaster tweet resources mainly provid
AI agents on foundation models often misapply healthcare and life sciences decision frameworks, citing the right guideline but applying it incorrectly. This post shares 38 open-source agent skills acr
arXiv:2609.16331v1 Announce Type: new Abstract: We present ManiSkillFormer, a neuro-symbolic framework for demonstration-free and compositional robotic manipulation. Instead of learning end-to-end vis
arXiv:2609.15992v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have rendered them necessary for Natural Language Processing (NLP) tasks, and their high inference cost
arXiv:2609.16527v1 Announce Type: cross Abstract: Exploring the chemical space of flexible molecules remains challenging because the vast number of possible compounds and conformations, together with
arXiv:2609.16930v1 Announce Type: cross Abstract: Deep Limit Order Book forecasting models capture nonlinear market dynamics, but their ability to quantify the effects of counterfactual order book mes
arXiv:2609.16563v1 Announce Type: cross Abstract: We have developed the MAL Simulator, a cyber operation simulator based on the Meta Attack Language (MAL). The MAL Simulator is intended for decision-d
arXiv:2609.16878v1 Announce Type: cross Abstract: Despite its crucial role in video object removal (VOR), existing evaluation paradigms face two critical limitations: questionable references and a mis
arXiv:2609.15131v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) require substantial computation to process numerous visual tokens across all transformer layers. Most methods
arXiv:2609.14756v1 Announce Type: new Abstract: Reliable path tracking is crucial for autonomous underwater vehicles (AUVs) operating in dynamic and uncertain marine environments. However, traditional
arXiv:2609.14343v1 Announce Type: new Abstract: Control barrier functions (CBFs) provide a mathematically grounded framework for enforcing local collision-avoidance constraints in autonomous mobile ro
arXiv:2609.12394v2 Announce Type: replace Abstract: Mobile GUI agents are shifting from multi-module frameworks to native models trained end-to-end, yet industrial deployment faces three persistent ga
arXiv:2609.14739v1 Announce Type: cross Abstract: Large language models are increasingly used in high-stakes domains such as law, where systems must ground their reasoning in retrieved evidence and ab
arXiv:2604.07487v2 Announce Type: replace Abstract: Large language model agents rely on effective model context to obtain task-relevant information for decision-making. Many existing context engineeri
arXiv:2601.00290v3 Announce Type: replace Abstract: Clinical trials constitute a critical yet exceptionally challenging and costly stage of drug development (2.6B per drug), where protocols are encode
arXiv:2609.13397v1 Announce Type: new Abstract: In rendering, a camera is a sampling operator that maps each finite pixel to a bundle of rays. Different camera models change the geometry of this bundl
arXiv:2609.15989v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is a safety strategy where the reasoning of a large language model 'actor' is inspected by a 'monitor' (often another
arXiv:2508.02312v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine t
arXiv:2512.08379v3 Announce Type: replace Abstract: Biosignals collected from wearable devices are widely utilized in healthcare applications. Machine learning models used in these applications often
arXiv:2603.02790v2 Announce Type: replace Abstract: Foundation models are changing the way we develop medical artificial intelligence. By learning broadly generalizable features across diverse data mo
arXiv:2609.14256v1 Announce Type: new Abstract: Topic models are widely used to analyze public health-related social media short texts, yet their evaluation remains dominated by metrics that focus ent
arXiv:2609.14466v1 Announce Type: new Abstract: Video segmentation models recognize and track objects over time, but they do not indicate whether each segmented region moves independently of the obser
arXiv:2609.15077v1 Announce Type: new Abstract: Molecular design is typically approached as a problem of finding molecules which can adopt a single bioactive conformation. In reality, molecules occupy
arXiv:2609.12839v2 Announce Type: replace-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posin
arXiv:2609.14654v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) are typically evaluated using held-out classification accuracy, an approach that presupposes predictions are based
arXiv:2609.13580v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across a wide range of natural language processing tasks. However, conventional fine-
arXiv:2609.14441v1 Announce Type: cross Abstract: Parkinson's disease (PD) manifests early neuromotor impairments that become observable in controlled hand-drawn patterns such as spirals and meanders,
arXiv:2609.14779v1 Announce Type: new Abstract: Performing deliberate mathematical reasoning in visual contexts is a hallmark of advanced Multimodal Large Language Models (MLLMs) and requires a sophis
arXiv:2609.13518v1 Announce Type: new Abstract: We present GeoTTER, a novel framework that redefines optimal transport in the realm of zero-shot classification. Conventional methods often suffer from
arXiv:2609.13466v1 Announce Type: new Abstract: Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifie
arXiv:2603.19308v2 Announce Type: replace-cross Abstract: In autonomous driving, multi-agent collaborative perception enhances sensing capabilities by enabling agents to share perceptual data. A key c
arXiv:2609.15134v1 Announce Type: new Abstract: Computer-use agents increasingly interact with browsers, terminals, file systems, and external services, introducing safety risks that emerge through ru
arXiv:2609.14770v1 Announce Type: cross Abstract: Generalisations are common in scientific communication, even though they are semantically ambiguous. An automated method is needed to identify and cat
arXiv:2609.13768v1 Announce Type: new Abstract: Multi-hop question answering often fails when retrieval treats evidence as isolated matches to the original question, since the facts needed to answer a
arXiv:2509.23043v2 Announce Type: replace-cross Abstract: Generative models have been extensively used to accelerate MCMC mixing for sampling and optimization, but their effective integration with sta
arXiv:2609.15770v1 Announce Type: new Abstract: Light detection and ranging (LiDAR) remains less explored than RGB-D sensing for perceptive legged locomotion, and existing LiDAR-based approaches often
For years, the JVM has watched the AI revolution from the bench. Every model, AI framework, every breakthrough, built with/for Python. jinfer is an inference engine built for the JVM from first princi
arXiv:2609.14268v1 Announce Type: new Abstract: In this work, we propose a decentralized communication-conditioned generative framework for multi-agent collision avoidance. Agents generate short-horiz
arXiv:2609.14058v1 Announce Type: new Abstract: In this work, we developed a nonlinear model predictive control (NMPC) framework that employs learned dynamics via the Koopman Operator theory for mobil
arXiv:2609.14072v1 Announce Type: new Abstract: Large Language Models (LLMs) have displayed impressive capabilities in handling tasks that require few demonstration examples, making them effective few
arXiv:2609.15611v1 Announce Type: cross Abstract: Molecular property prediction requires representations that generalize from limited labeled data to structurally novel compounds. Existing molecular p
arXiv:2501.18060v2 Announce Type: replace-cross Abstract: Conformal inference provides a rigorous statistical framework for uncertainty quantification in machine learning, enabling well-calibrated pre
arXiv:2602.06797v3 Announce Type: replace-cross Abstract: We study optimal learning rate (LR) schedules under the functional scaling law (FSL) framework (Li et al., 2025), which decomposes training dy
arXiv:2609.15344v1 Announce Type: new Abstract: We study the adaptation of pretrained language models to univariate time-series forecasting through a parameter-efficient transfer learning framework, w
arXiv:2609.14277v1 Announce Type: cross Abstract: Ringdown gravitational waves from binary black hole mergers can be modeled as superpositions of quasinormal modes (QNMs), whose frequencies and excita
arXiv:2609.13190v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring using photoplethysmography (PPG) offers a promising solution for personalized healthcare. However, ex
arXiv:2609.13566v1 Announce Type: new Abstract: Industrial maintenance systems involve multiple interacting assets and shared resources, making it challenging to balance reliability and operational co
arXiv:2609.13734v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in real-world high-stakes applications, effective governance has become essential. Existing
arXiv:2609.13251v1 Announce Type: new Abstract: Commercial and advertising images are frequently affected by poor framing, partially cropped subjects, truncated text or logos, and insufficient context
arXiv:2609.15847v1 Announce Type: cross Abstract: This paper proposes FREDI (Fair Resource Allocation for Edge Dual-Threshold Inference), a secure wireless edge-intelligence framework for event-trigge
arXiv:2609.13340v1 Announce Type: cross Abstract: Breast ultrasound imaging plays an important role in the early detection and diagnosis of breast cancer, particularly for patients with dense breast t
arXiv:2609.14100v1 Announce Type: cross Abstract: Fashion Image Captioning (FIC) plays a vital role in enhancing user experience and product search in e-commerce platforms. Unlike natural scene image
arXiv:2609.13851v1 Announce Type: cross Abstract: Post-training vision-language-action (VLA) models for specific robots and tasks requires in-domain demonstrations, yet collecting diverse robot data i