Knowledge catalogue
arXiv:2606.03655v1 Announce Type: new Abstract: Recent work in defeasible reasoning has seen notions of preferential semantics and entailment in the style of Kraus et al. applied to modal logics. Howe
arXiv:2606.03792v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) successfully enables personalization in text-to-image generation by adapting pre-trained diffusion models to specific visual
arXiv:2606.03112v1 Announce Type: cross Abstract: With the increasing scale and number of wind farms, wind turbines' daily operation and maintenance costs are increasing. To reduce operation and maint
arXiv:2606.02673v1 Announce Type: new Abstract: Graphs have been used to enhance large language models (LLMs) for structured reasoning, mostly as external knowledge sources are provided to models at t
arXiv:2509.19305v2 Announce Type: replace-cross Abstract: Diffusion probability models have shown significant promise in offline reinforcement learning by directly modeling trajectory sequences. Howev
arXiv:2606.02974v1 Announce Type: new Abstract: Human Activity Recognition (HAR) using WiFi signals has emerged as a transformative technology for smart homes, healthcare monitoring, security systems,
arXiv:2606.03063v1 Announce Type: cross Abstract: We propose ZX-Calculus (Knowledge Evolution Calculus), a conservative extension of Martin-Lof Dependent Type Theory (MLTT) integrating trace-indexed t
arXiv:2606.01057v1 Announce Type: cross Abstract: Procedural 3D modeling through code is emerging as a versatile paradigm, offering deterministic, engine-ready, and precisely editable assets that neur
arXiv:2606.01312v1 Announce Type: cross Abstract: The integration of Artificial Intelligence (AI) and emerging 6G networks introduces new opportunities for scalable coordination in tactical autonomous
arXiv:2606.02232v1 Announce Type: new Abstract: Learning a Markov transition model is not merely conditional density estimation: the learned object must be a valid transition kernel before it is itera
arXiv:2606.01092v1 Announce Type: cross Abstract: Supervised learning evaluates predictors through their input-output behavior. When a predictor is implemented as a composition f=circ h, supervised ev
arXiv:2606.00550v1 Announce Type: cross Abstract: The persistent challenge in scaling authentic manipulator education within university laboratories is a structural dichotomy: commercial digital twins
arXiv:2603.04256v3 Announce Type: replace Abstract: When the color distribution of input images changes at inference, the performance of conventional neural network architectures drops considerably. A
arXiv:2606.02296v1 Announce Type: new Abstract: Multi-robot systems cannot assume persistent network connectivity. We study this problem through target tracking, where performance depends on how quick
arXiv:2606.00889v1 Announce Type: cross Abstract: Phishing attacks remain a major cybersecurity threat, exploiting deceptive URLs to steal sensitive user information. Traditional blacklist and rule-ba
arXiv:2606.01069v1 Announce Type: new Abstract: Real-time emotion recognition from facial expressions is a challenging task, particularly in video-based scenarios where multiple emotional states may o
arXiv:2606.01861v1 Announce Type: new Abstract: Self-play, a type of training algorithm that enables a model to self-improve, has recently shown promising empirical results in the context of formal th
arXiv:2507.08038v3 Announce Type: replace-cross Abstract: Language model agents are increasingly used to automate scientific research, yet evaluating their scientific contributions remains a challenge
arXiv:2606.00518v1 Announce Type: new Abstract: Agentic AI systems can plan over multiple steps, use tools, and execute tasks over time. When such systems cause harm, tort law struggles to allocate re
arXiv:2606.01892v1 Announce Type: new Abstract: Robot localization systems are critical for autonomous navigation and safety. Adversarial perturbations can mislead these systems, resulting in mislocal
arXiv:2606.02551v1 Announce Type: cross Abstract: Affordance understanding bridges visual perception and physical action, serving as an explainable interface for robot manipulation in open and unstruc
arXiv:2606.01508v1 Announce Type: cross Abstract: Traditional operating systems were designed around deterministic programs, explicit control flow, and human initiated workflows. Their core abstractio
arXiv:2511.14460v2 Announce Type: replace Abstract: Large language models (LLMs) have rapidly evolved from single-turn text generators into the foundation of increasingly capable agents. As these agen
arXiv:2606.02461v1 Announce Type: new Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future e
arXiv:2606.02080v1 Announce Type: cross Abstract: Biological image analysis increasingly demands integration across heterogeneous tools, programming environments, and domain knowledge that few researc
arXiv:2606.00417v1 Announce Type: cross Abstract: To meet the stringent requirements of emerging applications and the increasingly complex network management and operation, the Next Generation Mobile
arXiv:2606.00093v1 Announce Type: new Abstract: Validating an LLM judge against human annotations usually means reporting several agreement statistics: accuracy, precision, recall, F_1, Cohen's kappa,
arXiv:2407.15510v2 Announce Type: replace Abstract: Abstraction is key to human and artificial intelligence as it allows one to identify common structure in otherwise distinct objects or situations. A
arXiv:2606.00386v1 Announce Type: new Abstract: Accurately modeling soft boundaries, e.g., hair and defocus blur, is a fundamental challenge in stereo conversion due to the ambiguous blending of foreg
arXiv:2606.01982v1 Announce Type: new Abstract: Schema-constrained information extraction from diverse educational and labor-market corpora remains an open challenge in natural language processing bec
At Google Cloud Next, we announced the preview of graph algorithms with Spanner Graph, bringing Google Research’s state-of-the-art graph mining capabilities natively to your database. These graph inte
arXiv:2606.00024v1 Announce Type: new Abstract: Long-context decoding in Large Language Models (LLMs) is severely constrained by the memory bandwidth required to fetch the extensive Key-Value (KV) cac
arXiv:2606.00602v1 Announce Type: new Abstract: Learning transferable and interpretable representations from medical volumetric scans remains challenging due to complex anatomical structures and weak,
arXiv:2606.01558v1 Announce Type: new Abstract: The effectiveness of Chain-of-Thought (CoT) prompting in Multimodal Large Language Models (MLLMs) remains uncertain: across several visual reasoning ben
arXiv:2606.00621v1 Announce Type: cross Abstract: Generative artificial intelligence has fundamentally changed how content is now produced. It has enabled how high-fidelity text, images, audio, and vi
arXiv:2604.03789v2 Announce Type: replace-cross Abstract: Recent advances in large language models have significantly improved their ability to perform mathematical reasoning, extending from elementar
arXiv:2606.02009v1 Announce Type: new Abstract: In Automated Essay Scoring (AES), benchmarking practices have fostered minimalist evaluation practices, in contrast with the broader-view recommendation
arXiv:2606.00383v1 Announce Type: cross Abstract: While Model Predictive Control (MPC) provides strong stability and robustness, it imposes a significant computational burden on real-time systems. Thi
arXiv:2606.00871v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used to generate structured descriptions of street-level imagery for tasks such as streetscape auditing
arXiv:2509.11056v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is anticipated to emerge as a pivotal enabler for the forthcoming sixth-generation (6G) wireless communication sy
arXiv:2601.18340v2 Announce Type: replace Abstract: As video generation models are increasingly expected to manipulate physical dynamics, there is a growing need to move evaluation beyond appearance f
arXiv:2606.00452v1 Announce Type: new Abstract: Dynamic scene reconstruction via 3D Gaussian Splatting (3DGS) has emerged as a compelling approach for representing evolving environments, yet understan
arXiv:2606.01095v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies and World-Action Models (WAM) represent two increasingly important paradigms for robotic manipulation. However,
arXiv:2606.00670v1 Announce Type: cross Abstract: Face-to-face speech comprehension is inherently multimodal, integrating acoustic signals with visible articulation, facial expression, head motion, an
arXiv:2606.00038v1 Announce Type: cross Abstract: Artificial intelligence (AI) literacy is increasingly recognized as a foundational competency for all university graduates. Yet students' engagement w
arXiv:2510.06048v4 Announce Type: replace Abstract: Effective data selection is essential for pretraining large language models (LLMs), enhancing efficiency and improving generalization to downstream
arXiv:2606.00193v1 Announce Type: new Abstract: The rapid spread of fake news on social media has become a major challenge, particularly in multilingual and under-resourced contexts such as North Afri
arXiv:2606.01237v1 Announce Type: new Abstract: Mild cognitive impairment (MCI) and subjective cognitive decline (SCD) are closely associated with the early Alzheimer's disease continuum, where accura
arXiv:2602.02470v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) have achieved remarkable success in many complex tasks, yet they can still fail in very simple logical r
arXiv:2407.01374v2 Announce Type: replace Abstract: Malaysian English is a low resource creole language, where it carries the elements of Malay, Chinese, and Tamil languages, in addition to Standard E
arXiv:2606.02497v1 Announce Type: new Abstract: Time series forecasting has advanced rapidly, especially with the emergence of foundation models that show strong zero-shot performance on numerical ext
arXiv:2510.27249v2 Announce Type: replace Abstract: Deep neural networks (DNNs) have achieved remarkable success in computer vision tasks such as image classification, segmentation, and object detecti
arXiv:2606.01437v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) are highly susceptible to adversarial perturbations, leading to extensive research on robustness for safety-critical appli
arXiv:2606.01298v1 Announce Type: new Abstract: The spread of hate speech has become increasingly harmful in modern digital environments, particularly on social networking platforms. While recent adva
arXiv:2606.01725v1 Announce Type: new Abstract: Agentic AI completes tasks through iterative planning, tool use, and reasoning based on observed outcomes. Despite its popularity, its system-level beha
arXiv:2510.11560v2 Announce Type: replace-cross Abstract: The advent of LLMs has given rise to generative search, a new search paradigm in which LLMs retrieve information from the web related to a que
arXiv:2509.14143v2 Announce Type: replace Abstract: Vision-language-action (VLA) models have recently emerged as a promising paradigm for robotic control, enabling end-to-end policies that ground natu
arXiv:2606.01951v1 Announce Type: new Abstract: Vision-language-action (VLA) models are promising for diverse robotic tasks, but their performance heavily depends on large-scale high-quality training
arXiv:2603.03202v3 Announce Type: replace Abstract: As large language models (LLMs) advance their mathematical capabilities toward the IMO and research level, the scarcity of challenging, high-quality
arXiv:2606.00658v1 Announce Type: cross Abstract: Large video diffusion models achieve strong visual quality but remain expensive to deploy because each sample requires many denoising steps and a larg