Knowledge catalogue
arXiv:2608.14856v1 Announce Type: cross Abstract: Computing Nash equilibria in interdependent security (IDS) games on networks is computationally expensive: best-response dynamics may need hundreds of
arXiv:2608.14722v1 Announce Type: new Abstract: Stroke remains a leading cause of mortality and morbidity worldwide, emphasizing the importance of its accurate and immediate assessment. Retinal fundus
arXiv:2608.15266v1 Announce Type: cross Abstract: Functional connectome analysis examines brain-region interactions to understand and identify disorders such as autism spectrum disorder and Alzheimer'
arXiv:2608.15893v1 Announce Type: new Abstract: The rise of social media bots poses a persistent threat, enabling misinformation, opinion manipulation, and the erosion of trust in online platforms. To
arXiv:2608.16010v1 Announce Type: cross Abstract: Model compression is critical for deploying networks on resource-constrained edge devices. While pruning-based methods can significantly reduce model
arXiv:2608.16681v1 Announce Type: cross Abstract: Although semi-supervised semantic segmentation (ext{S}^4) utilizes abundant unlabeled data to reduce manual labeling burdens, independent training of
arXiv:2502.14424v3 Announce Type: replace-cross Abstract: Most self-supervised learning objectives defend against collapse but leave the target representation law unspecified. We formulate representat
arXiv:2608.15772v1 Announce Type: new Abstract: When a language model refuses to answer a prompt, it is unclear whether the correct answer is erased from its internal representations, or merely suppre
arXiv:2511.17006v2 Announce Type: replace Abstract: Scaling test-time computation has been extended from language model reasoning to tool-augmented agents, where scaling involves not only thinking in
arXiv:2505.02763v2 Announce Type: replace-cross Abstract: One of the central promises of legal AI is to automate drudgery -- the formal, repetitive tasks of lawyers' work that consume time without cal
arXiv:2608.16594v1 Announce Type: new Abstract: Cancer survival prediction supports treatment planning, risk stratification, and follow-up management. Existing methods use structured clinical variable
arXiv:2608.16829v1 Announce Type: cross Abstract: Video world models approximate the stochastic distribution of physical outcomes through generative sampling, but existing benchmarks score individual
arXiv:2509.15035v2 Announce Type: replace Abstract: This study investigates the use of generative AI to support formative assessment through machine generated reviews of peer reviews in graduate onlin
arXiv:2608.14617v1 Announce Type: cross Abstract: A recurring proposal in legal AI is to improve case-outcome prediction by fusing uncertainty tools (evidence graphs with belief propagation, sequentia
arXiv:2608.16785v1 Announce Type: new Abstract: This paper proposes a calibration-free framework for reliably and effectively estimating vehicle speeds from monocular videos, without relying on roadwa
arXiv:2603.21933v2 Announce Type: replace-cross Abstract: The pruning of 3D Gaussian splats is essential for reducing their complexity to enable efficient storage, transmission, and downstream process
arXiv:2605.06264v2 Announce Type: replace Abstract: End-to-end autonomous driving models generate future trajectories from multi-view inputs, improving system integration but introducing opaque decisi
arXiv:2603.18334v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) increasingly assist secure software development, their ability to meet the rigorous demands of Rust program ve
arXiv:2608.14894v1 Announce Type: new Abstract: Machine-learning systems usually model external data, while their internal functional organization is analyzed by external observers. This work introduc
arXiv:2608.16855v1 Announce Type: new Abstract: Background Lung cancer remains the deadliest cancer worldwide because it is often diagnosed too late. Effective treatment depends on detection at an ear
arXiv:2608.16068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as agents that rely on system prompts to use tools and complete tasks. Such deployments impose
arXiv:2608.15831v1 Announce Type: cross Abstract: Remote photoplethysmography (rPPG) enables non-contact heart rate (HR) monitoring from facial videos, but RGB-only methods are vulnerable to illuminat
arXiv:2608.15574v1 Announce Type: cross Abstract: Video question answering systems built on vision-language models often produce timestamped claims with high confidence even when unsupported by the ci
arXiv:2608.15404v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) are designed to make visual classification interpretable by expressing predictions through human-understandable concept
arXiv:2608.14791v1 Announce Type: new Abstract: Abductive reasoning, often characterized as inference to the best explanation, is central to explanation under uncertainty, from everyday sense-making a
arXiv:2608.15046v1 Announce Type: new Abstract: A fraction of a point of benchmark accuracy is the usual evidence that a compressed model is equivalent to its original. That quantity is least informat
arXiv:2608.15110v1 Announce Type: cross Abstract: Emotional 3D talking head generation aims to synthesize expressive facial animations with accurate lip synchronization. However, existing methods ofte
arXiv:2608.14761v1 Announce Type: cross Abstract: At a finite public-chance cut, counterfactual regret minimization (CFR) must choose how many outcomes to evaluate before each regret update. Exact eva
arXiv:2608.15246v1 Announce Type: cross Abstract: Sparse-view computed tomography (CT) reduces radiation dose by acquiring fewer projection views, but the resulting inverse problem is highly ill-posed
arXiv:2608.15788v1 Announce Type: new Abstract: Spatial intelligence requires foundation models to maintain coherent spatial state across interactions with the physical world. However, existing data-c
arXiv:2608.15407v1 Announce Type: cross Abstract: An invariant behavioral profile is the defining vulnerability of traditional honeypot installations: a skilled adversary can confirm the presence of a
arXiv:2608.15843v1 Announce Type: cross Abstract: Characterising electrophysiological properties of cardiac tissue efficiently and accurately from spatially sparse intracardiac measurements is clinica
arXiv:2608.14581v1 Announce Type: cross Abstract: Thermal monitoring in practical applications is often constrained by sparse sensing, measurement noise, and limited spatial resolution, which hinder t
arXiv:2608.14630v1 Announce Type: cross Abstract: Human decision-making is often shaped by a range of well-documented cognitive biases. As large language models (LLMs) become increasingly integrated i
arXiv:2608.16666v1 Announce Type: new Abstract: This paper presents Chronocooked, a reinforcement learning (RL) benchmark suite for studying implicit interval timing in RL agents. Inspired by Overcook
arXiv:2608.15905v1 Announce Type: new Abstract: Hateful video detection has become increasingly important with the rapid growth of video-centric social media platforms, given the serious risks that ha
arXiv:2608.14737v1 Announce Type: cross Abstract: This study analyses LLMs in imbalanced binary classification, using study screening in systematic reviews as the application domain. An experiment was
arXiv:2608.16286v1 Announce Type: new Abstract: While various organizations now actively encourage LLM use in classrooms, we still lack rigorous, systematic evaluations of how well these models actual
arXiv:2608.16798v1 Announce Type: cross Abstract: Agent harnesses have substantially improved performance on long-horizon tasks by coordinating agent interactions with the environment. However, reinfo
arXiv:2608.16686v1 Announce Type: cross Abstract: Empathetic social robots should respond not only to what users say, but also to how their emotions dynamically evolve during interaction. However, exi
arXiv:2602.12756v2 Announce Type: replace Abstract: Large Language Models (LLMs) have recently shown exceptional potential in time series forecasting (TSF), leveraging their inherent sequential reason
arXiv:2608.15972v1 Announce Type: cross Abstract: Synchronized camera and wireless measurements observe the same scene through different physical channels. The central difficulty is that a representat
arXiv:2608.16555v1 Announce Type: new Abstract: Recent advances in AI technologies have enabled the advanced design of complex control policies. In contrast, focusing on the body, many robots still em
arXiv:2608.14570v1 Announce Type: new Abstract: Understanding human mobility is critical for a wide range of urban applications, including traffic management, epidemic control, and urban planning. How
arXiv:2608.16126v1 Announce Type: cross Abstract: Identification of dominant polynomial-chaos modes is usually formulated as a sparse-regression problem on a sampled multivariate polynomial dictionary
arXiv:2608.16268v1 Announce Type: new Abstract: Medical foundation models improve generalization when training AI models with limited labeled data, but remain confined to a single specialty, such as p
arXiv:2608.14963v1 Announce Type: cross Abstract: Pareto Conditioned Networks learn multiple multi-objective reinforcement learning behaviours by conditioning a single policy on a desired return comma
arXiv:2608.16207v1 Announce Type: new Abstract: Consider a firm that surveys its competition for a particular agentic task and seeks to offer superior accuracy at every competitor price point. A firm
arXiv:2608.16246v1 Announce Type: cross Abstract: Autonomous AI agents tackling Long Horizon Tasks depend on marketplace skills that are certified one at a time: a scanner returns a safety verdict for
arXiv:2511.11427v2 Announce Type: replace Abstract: Referring Expression Comprehension (REC) requires models to localize objects in images based on different types of natural language descriptions. Ev
arXiv:2608.15915v1 Announce Type: cross Abstract: Lung cancer remains the leading cause of cancer-related mortality worldwide, while histopathological diagnosis is often affected by inter-observer var
arXiv:2510.15042v3 Announce Type: replace Abstract: In the 3D medical image domain, vision-language pre-training is used to create vision-language encoders (VLEs) that can support radiologists by retr
arXiv:2608.16467v1 Announce Type: cross Abstract: The qualitative research methodologies that underpin consumer-insight generation - the KJ method, Grounded Theory, and Thematic Analysis - share a str
arXiv:2606.12654v2 Announce Type: replace-cross Abstract: We develop a new, differentially private mean estimator called the balloon mean. The main features of the balloon mean are that it is computat
arXiv:2608.16669v1 Announce Type: new Abstract: Recent advances in pathology foundation models have enabled accurate prediction of spatial transcriptomics (ST) from routine H&E images. However, existi
arXiv:2608.15698v1 Announce Type: new Abstract: Visual document retrieval is a critical component of multimodal retrieval-augmented generation, aiming to identify query-relevant pages from document co
arXiv:2608.16210v1 Announce Type: new Abstract: Aggregate accuracy hides where models succeed and fail. Estimating conditional performance profiles from gold labels alone is expensive, while cheap aux
arXiv:2501.12434v3 Announce Type: replace-cross Abstract: Motivation: Retrosynthesis plays a crucial role in organic synthesis and drug discovery, focusing on identifying a set of reactants capable of
arXiv:2608.15147v1 Announce Type: new Abstract: Machine intelligence has conquered the symbolic world but stalled at the physical one. The stall is structural: physical AI faces a cold-start deadlock
arXiv:2608.15109v1 Announce Type: new Abstract: Generating structurally valid synthetic tabular data remains difficult: outputs with high statistical fidelity and downstream utility can still violate