Knowledge catalogue
arXiv:2608.22887v1 Announce Type: new Abstract: Large language models (LLMs) are entering decisions in triage and lending, where task-relevant inference must be distinguished from impermissible proxy
arXiv:2608.23463v1 Announce Type: new Abstract: The quadratic growth of attention computation and key-value (KV) cache with respect to sequence length is a central bottleneck for ultra-long-context la
arXiv:2608.21874v1 Announce Type: cross Abstract: Deep learning has achieved strong performance in encrypted traffic classification (ETC), yet its computational cost limits deployment on resource-cons
arXiv:2608.23028v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in education, healthcare, policy advising, and other interactive settings, where users engage the
arXiv:2608.21853v1 Announce Type: new Abstract: Large language models are increasingly moving beyond text processing, adding support for other modalities such as images and audio. While text understan
arXiv:2608.22636v1 Announce Type: new Abstract: Q-learning with linear function approximation can be unstable because an arbitrary approximation architecture need not preserve the Bellman contraction.
arXiv:2504.03337v2 Announce Type: replace Abstract: Existing bias mitigation methods for Visual Question Answering (VQA), a typical Artificial intelligence application, endure two main limitations. Fi
arXiv:2608.22937v1 Announce Type: new Abstract: Quality control during printed circuit board (PCB) assembly is a critical step in ensuring reliable electronic products. Detecting misaligned pins durin
arXiv:2412.07264v2 Announce Type: replace-cross Abstract: Understanding complex animal behaviors hinges on deciphering the neural activity patterns within brain circuits, making the ability to forecas
arXiv:2608.21567v1 Announce Type: new Abstract: Human mobility serves as an essential proxy for understanding social, economic, and environmental dynamics in urban systems. Geospatial transferability,
arXiv:2608.22475v1 Announce Type: new Abstract: We study parameterized quantum circuits (PQCs) integrated as residual sidecar modules within a ResNet-50 backbone for 31-class neural population decodin
arXiv:2608.23119v1 Announce Type: cross Abstract: We study a hybrid proposal--correction architecture for reduced-order PDE forecasting in which a pure-state quantum reservoir computer (QRC) predicts
arXiv:2608.22214v1 Announce Type: new Abstract: In domain-specific multimodal long documents, images and text jointly convey complex knowledge that cannot be fully captured by plain text alone. Howeve
arXiv:2608.22678v1 Announce Type: cross Abstract: UAV vision-language navigation (UAV-VLN) is commonly evaluated as goal reaching, but inspection-oriented deployment requires the agent to stop within
arXiv:2608.23468v1 Announce Type: new Abstract: Anomaly detection is often applied to data stored in relational databases, yet most existing methods require flattening multiple tables into a single fe
arXiv:2608.22118v1 Announce Type: new Abstract: LLM responses are based on the internet (via training or RAG), and AI is now used to generate a significant amount of content online (Paredes et al., 20
arXiv:2608.21597v1 Announce Type: cross Abstract: Clinical data sources such as electronic health records and wearable sensors record patient status repeatedly over follow-up, often at irregular times
arXiv:2608.22432v1 Announce Type: cross Abstract: Multilingual LLM judges produce different evaluator-backbone rankings depending on the prompt language: on an eight-language Agent-as-a-Judge benchmar
arXiv:2608.21591v1 Announce Type: new Abstract: Multi-horizon rare-event forecasting is hard under long macroeconomic series' data constraints: labeled events are scarce, and standard uncertainty quan
arXiv:2608.22237v1 Announce Type: new Abstract: Long-horizon agents increasingly rely on repeated access to external artifacts, yet current reading interfaces often expose entire objects even when onl
arXiv:2608.21677v1 Announce Type: cross Abstract: Recent mesh-based simulation advances have, in no small part, relied on neural surrogates of two distinct families: global models that route informati
arXiv:2608.21582v1 Announce Type: new Abstract: World models built on the RSSM architecture, such as DreamerV3, keep a recurrent hidden state h_t trained only to reduce prediction error. We show this
arXiv:2608.22071v1 Announce Type: cross Abstract: Turn-taking is a basic organizational feature of human conversation and remains difficult to model in natural, synchronous dialog systems. While exist
arXiv:2608.22329v1 Announce Type: cross Abstract: Emotion-aware artistic image generation requires a model to satisfy semantic content, artistic style, and target emotion simultaneously. The key chall
arXiv:2505.17571v2 Announce Type: replace Abstract: Personalization is a critical task in modern intelligent systems, with applications spanning diverse domains, including interactions with large lang
arXiv:2608.22786v1 Announce Type: new Abstract: Multimodal graph learning requires jointly training over graph structure and heterogeneous node attributes, yet existing methods largely decouple these
arXiv:2608.22334v1 Announce Type: cross Abstract: Near a smooth data manifold, one tangent space summarizes local geometry. At a branch point, the corresponding first-order object is instead a measure
arXiv:2608.21985v1 Announce Type: new Abstract: As the adoption of large language models (LLMs) grows in Arabic-speaking regions, ensuring their safety and cultural alignment is increasingly critical.
arXiv:2503.09130v2 Announce Type: replace-cross Abstract: This paper presents InteractEdit, a novel framework for reference-free Human-Object Interaction (HOI) editing that tackles the challenging tas
arXiv:2608.21881v1 Announce Type: new Abstract: We describe our approach to the Big Cross-Modal Attenuation Correction (BIC-MAC) challenge, which asks for a pseudo-CT in Hounsfield Units to be synthes
arXiv:2608.22335v1 Announce Type: cross Abstract: Bengali is the seventh-most-spoken language globally, yet LLM safety evaluation remains overwhelmingly English-centric. We introduce BanglaSafe, a ben
arXiv:2608.21727v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is deployed to make models better at reasoning tasks, but its side effect on what models will di
arXiv:2603.06813v2 Announce Type: replace Abstract: In a stationary decentralized Markov game, learning peers generate an episode-indexed sequence of induced MDPs for any focal agent. The joint game r
arXiv:2606.14892v2 Announce Type: replace Abstract: An artificial intelligence must have a model of its environment that is causal, supporting reasoning about interventions and counterfactuals, and al
arXiv:2608.21482v1 Announce Type: cross Abstract: Background: Multimodal fracture classifiers may benefit from patient and anatomical metadata, but they can also become brittle when contextual informa
arXiv:2608.22042v1 Announce Type: new Abstract: General anesthesia offers a rare opportunity to observe the human brain under a standardized, controlled perturbation. Yet intraoperative electroencepha
arXiv:2608.21964v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over evolving software repositories, where success depends on repository-specific procedural know
arXiv:2608.22799v1 Announce Type: cross Abstract: We present the NeuralNexus Arm, an open, low-cost 6-DOF robotic manipulator built by an undergraduate engineering team, together with the design decis
arXiv:2608.23048v1 Announce Type: new Abstract: Semi-structured N:M sparsity has emerged as a practical direction for accelerating large language models (LLMs). However, existing learnable-mask approa
arXiv:2307.00379v2 Announce Type: replace Abstract: Driven by the need for more efficient and seamless integration of physical models and data, physics-informed neural networks (PINNs) have seen a sur
arXiv:2608.21815v1 Announce Type: new Abstract: Causal discovery on topological event sequences is crucial for ensuring the reliability of networks. However, existing methods struggle to capture the c
arXiv:2608.22914v1 Announce Type: new Abstract: This report summarizes the contributions and results of the 1st Asynchronous CASTLE Challenge at the Joint Egocentric Vision Workshop in conjunction wit
arXiv:2608.21626v1 Announce Type: new Abstract: Semantic communication shifts the objective of communication systems from accurate symbol reconstruction toward meaning preservation, task accomplishmen
arXiv:2608.23241v1 Announce Type: cross Abstract: Identifying and classifying environmental mitigation obligations in Federal Energy Regulatory Commission hydropower licensing documents is a labor-int
arXiv:2608.21970v1 Announce Type: new Abstract: Two-photon calcium imaging presents a challenging setting for foundation models: image appearance varies substantially across recordings and experimenta
arXiv:2608.21417v1 Announce Type: new Abstract: Flexible manufacturing requires industrial robots to be reprogrammed rapidly as product variants change. This paper presents a language-model-based work
arXiv:2608.21494v1 Announce Type: cross Abstract: Recent works have highlighted the expressive limitations of embedding based retrieval models through both theoretical analyses and challenging benchma
arXiv:2507.17448v2 Announce Type: replace-cross Abstract: Retrosynthetic planning is a cornerstone of organic synthesis and drug discovery. Yet existing AI methods often rely on pattern matching rathe
arXiv:2608.21366v1 Announce Type: new Abstract: Driven by massive amounts of web-scale data, generative AI (GenAI) has achieved remarkable progress, enabling various applications in diverse sectors. T
arXiv:2608.23452v1 Announce Type: cross Abstract: Space robots operate in extreme environments where hardware degradation can critically compromise traditional control strategies. While continual rein
arXiv:2608.23565v1 Announce Type: new Abstract: An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control
arXiv:2608.21379v1 Announce Type: new Abstract: Student burnout is highly prevalent in higher education, with reported rates ranging from 12% to over 70% and consistently exceeding those of the workin
arXiv:2608.22849v1 Announce Type: new Abstract: Full-length RNAs, particularly messenger RNAs, often exceed the context lengths used to pretrain existing RNA foundation models, limiting complete-trans
arXiv:2608.23395v1 Announce Type: cross Abstract: Recent LLM-agent systems make conflicting design bets: decompose work across many narrow agents, or use one strong tool-using agent. This pilot studie
arXiv:2608.22227v1 Announce Type: new Abstract: Reinforcement Learning (RL) has achieved tremendous success in recent years. However, the classical foundations of RL do not account for the risk sensit
arXiv:2608.21414v1 Announce Type: cross Abstract: Autonomous driving risk identification aims to determine which observed object is likely to become safety-critical to the ego vehicle. Existing approa
arXiv:2608.23040v1 Announce Type: new Abstract: RoboRacer offers a standardized platform for research using 1:10-scale autonomous vehicles, but the variety of available tracks hinders the process of a
arXiv:2608.21380v1 Announce Type: cross Abstract: With the increased adoption of robotic agents operating in human environments by scanning and sharing 3D representations (e.g., for fleet learning, cl
arXiv:2608.22419v1 Announce Type: cross Abstract: Query-based Vision-Language-Action (VLA) models offer low-latency inference that is attractive for bimanual robotic manipulation, but we observe that
arXiv:2608.22054v1 Announce Type: new Abstract: Structure-from-Motion (SfM) aims to estimate camera poses and reconstruct 3D structures from a collection of unordered images. Compared with incremental