Knowledge catalogue
arXiv:2608.18573v1 Announce Type: new Abstract: Existing explainable deepfake forensic methods typically rely on task-adapted MLLM to jointly address detection, localization, and explanation. Inspired
arXiv:2608.18625v1 Announce Type: cross Abstract: Cable-suspended payload transport by multirotor UAVs is flexible but generates periodic swing disturbance that degrades tracking and risks instability
arXiv:2608.18627v1 Announce Type: new Abstract: No-reference point cloud quality assessment (PCQA) has been an active topic in recent years and is used to measure and optimize the visual experience of
arXiv:2608.18438v1 Announce Type: cross Abstract: Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a 'supervision gap' where novice therapists manage high
arXiv:2608.18555v1 Announce Type: cross Abstract: Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environme
arXiv:2608.18085v1 Announce Type: new Abstract: Prior work has shown that large language models (LLMs) can express diverse personality traits in open-ended text generation. However, it remains unclear
arXiv:2602.08326v2 Announce Type: replace Abstract: Driving without considering the preferred separation distance from surrounding vehicles may cause discomfort for users. To address this limitation,
arXiv:2608.19121v1 Announce Type: cross Abstract: Improving molecular properties, such as drug-likeness or binding affinity, is a recurring task in early-stage drug discovery. However, molecules optim
arXiv:2608.18495v1 Announce Type: cross Abstract: Radio maps are essential for wireless decision-making tasks such as access-point placement, coverage planning, and localization, but their fine spatia
arXiv:2508.15436v2 Announce Type: replace-cross Abstract: We propose a extbf{P}latform for extbf{L}ayout-extbf{A}ware extbf{S}earch and extbf{M}emory extbf{A}rrangement (extbf{PLASMA}), a unified eval
arXiv:2608.18117v1 Announce Type: new Abstract: This position paper argues that AI leaderboards are structurally ill-suited to serving the Global South because they lack independent governance, confli
arXiv:2608.18081v1 Announce Type: new Abstract: Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time.
arXiv:2608.18078v1 Announce Type: new Abstract: This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be requi
arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Althoug
arXiv:2608.18092v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) promise scalable collaboration, yet adding agents often reduces reliability. This position paper argues that many MA
arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying tran
arXiv:2608.19147v1 Announce Type: cross Abstract: Modern Intel AI PCs ship capable integrated GPUs and NPUs with 16+ GB of unified memory, and they spend considerable time idle. That is not enough mem
arXiv:2606.14870v2 Announce Type: replace-cross Abstract: Foundation models (FMs) trained on large datasets and fine-tuned on downstream tasks have emerged as a powerful paradigm in AI for science. In
arXiv:2608.18631v1 Announce Type: new Abstract: As large language models evolve into decision-making agents, the ability to reason over preferences becomes fundamental to alignment, coordination, and
arXiv:2608.19115v1 Announce Type: new Abstract: Modern pretrained encoders make representations from heterogeneous views increasingly reusable, but the procedure that determines view utility and combi
arXiv:2608.18523v1 Announce Type: cross Abstract: Diffusion-based generators have made synthetic images ubiquitous, but detectors often fail under simultaneous shifts in generator, prompt/style, and s
arXiv:2608.18431v1 Announce Type: cross Abstract: This paper develops a computational framework to optimize the process parameters such that the bond quality between extruded polymer filaments is maxi
arXiv:2512.14012v2 Announce Type: replace-cross Abstract: The rise of AI agents is transforming how software can be built. The promise of agents is that developers might write code quicker, delegate m
arXiv:2608.18647v1 Announce Type: new Abstract: Autonomous endovascular navigation could support the delivery of mechanical thrombectomy to underserved areas, but controllers must navigate long, multi
arXiv:2608.18643v1 Announce Type: new Abstract: Researchers often choose a proxy dataset from many releases, transformations, or seeds. Search can make an invalid release appear adequate, while one ad
arXiv:2608.18659v1 Announce Type: cross Abstract: Tsetlin Machines (TMs) learn interpretable Boolean clauses using finite-state automata. We introduce the Quantum-Logic Tsetlin Machine (QL-TM), which
arXiv:2608.18901v1 Announce Type: cross Abstract: Tensor Networks are a relatively new machine learning approach. The architectures proposed initially are inspired by approaches from quantum many-body
arXiv:2608.18285v1 Announce Type: cross Abstract: 3D scene representation techniques such as neural radiance fields (NeRFs) and Gaussian splatting have made substantial progress in novel view synthesi
arXiv:2608.18165v1 Announce Type: new Abstract: Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical s
arXiv:2608.18768v1 Announce Type: new Abstract: Large language models are widely used to simulate survey respondents, yet their answers are homogeneous and unfaithful to real inter-group differences.
arXiv:2608.18552v1 Announce Type: new Abstract: This paper presents a real-time control-constrained Differential Dynamic Programming (DDP) framework for underactuated legged robots. To address the lim
arXiv:2405.15336v2 Announce Type: replace Abstract: Continuum robots are slender, flexible manipulators that navigate confined, curved workspaces and are gaining traction in aerospace, inspection, aut
arXiv:2608.18260v1 Announce Type: new Abstract: Large Language Models (LLMs) are being increasingly used in everyday applications. A major challenge in the context of LLMs or Artificial Intelligence (
arXiv:2608.18952v1 Announce Type: cross Abstract: Large language models can improve recommendation quality by reasoning explicitly over user history and candidate items - for example, extracting a use
arXiv:2608.18742v1 Announce Type: cross Abstract: In some fields currently dominated by empirical approaches, such as state of health (SoH) prediction for lithium-ion batteries, phenomenological model
arXiv:2608.18669v1 Announce Type: new Abstract: Humans solve complex problems by constructing plans and mentally simulating their outcomes with an internal model of the world. Machine learning has pro
arXiv:2511.12850v2 Announce Type: replace Abstract: Topic models are often judged by the consistency of their outputs across repeated runs, implicitly assuming that repeatable topic output is a succes
arXiv:2608.18317v1 Announce Type: new Abstract: Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction m
arXiv:2608.18271v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own responses using token-level supervision from the same model conditioned on privileged ref
arXiv:2608.18227v1 Announce Type: new Abstract: Push-T is an iconic benchmark for learning manipulation policies from human demonstrations. The robot must use a single point of contact to push a T-sha
arXiv:2608.19075v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate, generating content that the input image does not support. Preventing such content during decod
arXiv:2608.18593v1 Announce Type: new Abstract: Single-image rephotography aims to synthesize new shots of a scene from a single reference image with specified viewpoints, focal lengths, and photograp
arXiv:2608.18948v1 Announce Type: new Abstract: Collecting robot hand-object interaction data is costly and embodiment-specific, yet abundant human-object videos remain unusable for robot training. We
arXiv:2608.19073v1 Announce Type: new Abstract: An agent still learning its environment should be cautious while ignorant and bold once confident. The entropic value-at-risk captures this through a ro
arXiv:2607.15048v2 Announce Type: replace Abstract: Road surface mapping plays a crucial role in autonomous driving, supporting high-definition map generation, lane-level perception, and automatic roa
arXiv:2608.18410v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models process long multimodal token sequences, making inference expensive in both memory and computation. Existing efficie
arXiv:2607.16230v2 Announce Type: replace-cross Abstract: Accurate pre-order shipping cost estimation is important in e-commerce because it affects price presentation, margin planning, and conversion.
arXiv:2608.18682v1 Announce Type: new Abstract: Training multi-turn agentic workflows with reinforcement learning (RL) enables large language models to perform complex reasoning, use external tools, a
arXiv:2608.18864v1 Announce Type: new Abstract: LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typica
arXiv:2608.18190v1 Announce Type: new Abstract: Domain adaptation is widely used to make neural networks trained on simulations applicable to experimental data. Its premise is that the two domains dif
arXiv:2608.18131v1 Announce Type: new Abstract: Current safety alignment training for Large Language Models (LLMs) are heavily English-centric. When such safety filters fail for non-English languages,
arXiv:2608.18640v1 Announce Type: new Abstract: Long-term video object segmentation (VOS) remains challenging due to error accumulation under extended occlusions, re-appearance, and scene changes. Alt
arXiv:2608.18108v1 Announce Type: cross Abstract: Large language models are being incorporated into sensitive and important decision-making processes across nearly all fields. While prior work studies
arXiv:2608.18677v1 Announce Type: new Abstract: Amid concerns that generative AI may standardize art interpretation, this paper examines whether LLM-based interaction can support plural art-historical
arXiv:2608.18611v1 Announce Type: new Abstract: Electric power networks are increasingly exposed to weather-sensitive failure mechanisms that require asset-level, spatially explicit risk modelling for
arXiv:2608.18140v1 Announce Type: new Abstract: We define an intertwined scheduling and routing problem where new jobs appear due to the degradation of the existing jobs. Specifically, once a job arri
arXiv:2608.18508v1 Announce Type: cross Abstract: We are witnessing an explosion of agentic systems for computational chemistry simulations: from half a dozen in 2024 to a dozen in 2025, and the curre
arXiv:2608.19134v1 Announce Type: new Abstract: Accurate visual decoding can reveal how the brain represents visual information and recover perceived content from neural signals such as electroencepha
arXiv:2608.18918v1 Announce Type: new Abstract: Dimension reduction for dynamical systems is standard practice, and the standard route is spectral: model the transfer (Koopman) operator by its leading
arXiv:2608.18174v1 Announce Type: cross Abstract: Customer decline early-warning systems feed account-manager action lists, and every flagged account consumes intervention capacity. In a deployed busi