Knowledge catalogue
arXiv:2610.13730v1 Announce Type: new Abstract: Origin-destination (OD) flow forecasting supports urban mobility decisions by predicting the volume and patterns of human movement across a city. Most e
separating artifacts from the agent makes sense for sharing and cross-AI collaboration No vendor lock-in for your artifacts. Sites, decks, 3D games, reports, dashboards and galleries. Artifacts on Fly
arXiv:2610.13819v1 Announce Type: new Abstract: In clinical practice, experts often begin by converting raw inputs into a set of expert features before making a decision. While black-box models traine
arXiv:2610.13207v1 Announce Type: new Abstract: Fake news detection under low resource conditions is challenged by the scarcity of labeled data and the difficulty of capturing subtle deceptive pattern
arXiv:2610.13766v1 Announce Type: cross Abstract: Geospatial foundation models can support disaster damage assessment, but high accuracy on familiar disasters may hide shortcut learning: prediction fr
arXiv:2610.13524v1 Announce Type: new Abstract: Intermittent ``spikes'' in loss, during the pre-training of Large Language Models (LLMs), remains a mysterious phenomenon both theoretically and empiric
arXiv:2610.13571v1 Announce Type: new Abstract: We study simultaneous competitive and regret guarantees for TCP acknowledgment. Each acknowledgment serves all pending packets, and the objective is to
arXiv:2610.12975v1 Announce Type: new Abstract: We present SmartSalesBench, the first multi-turn conversational benchmark explicitly designed to evaluate large language model (LLM) sales agents agains
arXiv:2610.13740v1 Announce Type: cross Abstract: World-action models (WAMs) predict a robot's actions together with the observations those actions will produce. However, the strongest models rely on
arXiv:2610.13157v1 Announce Type: new Abstract: Reinforcement learning (RL) for search agents often suffers from evidence fabrication, a failure mode where agents bypass external information (E_{ext})
arXiv:2610.03994v2 Announce Type: replace-cross Abstract: VeriContest is a benchmark of 1007 competitive-programming problems in Rust, each with a Verus specification, a judge-accepted solution, and a
arXiv:2610.13614v1 Announce Type: cross Abstract: We discuss three simple connections between generative diffusion and optimal transport. First, the joint law of the data and of their Ornstein-Uhlenbe
arXiv:2610.13300v1 Announce Type: cross Abstract: Modeling human reactions to spatial audio requires understanding both what is heard and where it comes from. Prior work generates motion offline from
Bloomberg: Sources: DeepSeek agrees to lead robotic AI startup Winverse AI's seed funding round of tens of millions of dollars, valuing the startup at ~$400M post-money — DeepSeek aims to lead the fir
Nikkei Asia: Sources: NTT Data is in advanced talks to build an up to 500 MW data center for Anthropic in Osaka, among Japan's largest, potentially costing $6.3B — TOKYO/OSAKA — NTT Data Group is in t
Tony Diver / Telegraph: Sources: the US restores the UK AISI's access to the latest US models for safety testing, after ordering OpenAI and Anthropic to stop sharing models last month — US had blocked
arXiv:2610.12696v1 Announce Type: new Abstract: Vision-language-action models (VLAs) offer a promising route toward general-purpose robotics by transferring semantic knowledge from large-scale vision-
arXiv:2610.13051v1 Announce Type: cross Abstract: Some backdoor attacks never touch an image. FLIP only changes labels: on CIFAR-10, flipping 3% of them makes a ResNet-32 send 99.7% of triggered sourc
arXiv:2610.13812v1 Announce Type: new Abstract: Flow-matching and diffusion models are increasingly used as priors for linear inverse problems, however, most methods are bespoke to one class of trajec
arXiv:2610.12924v1 Announce Type: cross Abstract: We study dictionary learning for probability measure-valued data by embedding measures into Hilbert spaces using features derived from optimal transpo
arXiv:2610.12723v1 Announce Type: new Abstract: Neural surrogates that forecast a physical field from sparse, noisy sensors read a window of nearby sensors and a history of past snapshots. Practitione
arXiv:2610.13832v1 Announce Type: cross Abstract: When solving complex spatial reasoning tasks, ordinary humans naturally revisit the scenes from task-relevant viewpoints and mentally reconstruct the
arXiv:2610.13835v1 Announce Type: new Abstract: An ideal (language) model must continually update its knowledge. Existing work largely focuses on making these updates efficient after training. We inve
arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a
arXiv:2610.13945v1 Announce Type: new Abstract: A user who brings a generalist manipulation policy into their home or office wants it to pick up their objects from their shelves, counters, and tables.
arXiv:2610.13461v1 Announce Type: new Abstract: AI systems are making rapid progress in mathematics, but this progress is hard to measure. Benchmarks of solved problems saturate, and in benchmarks of
arXiv:2604.06058v2 Announce Type: replace-cross Abstract: Safety-critical control of uncertain, adaptive systems often relies on conservative, worst-case uncertainty bounds that limit closed-loop perf
arXiv:2610.12599v1 Announce Type: new Abstract: Sparse computation can scale the parametric capacity of LLMs without proportionally increasing active computation, but pretraining sparse architectures
arXiv:2610.13238v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has emerged as a powerful paradigm for transferring reasoning capabilities from frontier models to smaller models, while ex
arXiv:2610.12744v1 Announce Type: new Abstract: Parameter-efficient continual learning updates a restricted subset of adapter parameters to incorporate sequential tasks while limiting catastrophic for
arXiv:2610.12734v1 Announce Type: cross Abstract: Stereo vision is increasingly used for robotic manipulation, with a growing body of work incorporating it into Vision-Language-Action (VLA) models. Ho
I've been tuning llama.cpp on my Strix Halo box (Radeon 8060S, 128 GB) and the numbers are good enough to share. It's a branch called rdna35-perf on top of halo-box/strix-llama.cpp, a llama.cpp fork a
arXiv:2610.12532v1 Announce Type: cross Abstract: Generative creative interfaces routinely report the user's position within a space of possibilities. Such displays imply that the quantities shown wer
arXiv:2610.13896v1 Announce Type: new Abstract: Neural semantic parsers generate meaning representations token by token, yet well-formedness depends on references, scope, and graph relations that unfo
arXiv:2610.13306v1 Announce Type: new Abstract: Local online training on resource-constrained platforms requires low computational and training-state overhead. We study the numerical stability and com
arXiv:2610.13840v1 Announce Type: new Abstract: Comics are one of the great visual records of the twentieth century: hundreds of thousands of pages in which a mass readership saw its leaders, its wars
arXiv:2610.13750v1 Announce Type: new Abstract: Basic mathematical tasks like modular addition have been a valuable tool for illuminating aspects of neural network behavior that are challenging to see
Brock E.W. Turner / Axios: Suki, an AI ambient scribe for healthcare providers, raised a 90M Series E led by Healthier Capital; a source says it projects 60M-80M in revenue this year — Suki, a health
Sure does look like @GavinSBaker is “suggesting that public companies are materially inflating their remaining performance obligations”. yet another way the Ai industry is trying to con retail investo
arXiv:2610.12939v1 Announce Type: cross Abstract: Decoder hidden states from different layers of large language models (LLMs) often encode complementary information. However, existing speculative deco
arXiv:2510.07832v2 Announce Type: replace-cross Abstract: Spatial prediction refers to the estimation of unobserved values from spatially distributed observations. Although recent advances have improv
arXiv:2610.13307v1 Announce Type: new Abstract: The escalating environmental footprint of the Information and Communication Technol- ogy (ICT) sectorwith global Data Center electric- ity usage potenti
arXiv:2610.13356v1 Announce Type: new Abstract: Coding agents are increasingly deployed for end-to-end software engineering tasks, where a readily available oracle evaluator that defines the success c
arXiv:2610.13626v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used throughout the software development lifecycle. This growing reliance on LLMs raises concerns about
arXiv:2610.12569v1 Announce Type: new Abstract: Static coding benchmarks are fixed at release. Over time their tasks leak into training data, and stronger agents eventually saturate them. We argue tha
arXiv:2610.13081v1 Announce Type: new Abstract: Recent work on large audio-language models (LALMs) explores adaptive reasoning to balance accuracy and efficiency. However, existing approaches often re
arXiv:2610.12651v1 Announce Type: new Abstract: LLM agents executing multi-step workflows fail in two fundamentally different ways: recoverable slips, which further attempts can repair, and knowledge
arXiv:2610.13818v1 Announce Type: new Abstract: Representations of supervised datasets support higher-level machine-learning tasks such as dataset retrieval and distribution-shift monitoring. However,
arXiv:2610.13654v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular for their strong predictive performance. Many also provide posterior predictive distributions
arXiv:2610.13253v1 Announce Type: cross Abstract: In-context-learning Tabular Foundation Models (TFMs) are uniquely suited to scenarios with limited resources or privacy constraints, as they solve new
arXiv:2610.12790v1 Announce Type: new Abstract: Reliable robotic manipulation requires maintaining a firm grasp while strictly avoiding both contact slip and structural damage to the object. Satisfyin
arXiv:2610.13325v1 Announce Type: cross Abstract: Agentic workloads resend long contexts that barely change between calls. Prefix caching now skips most of their prefill, yet every request must still
arXiv:2610.12877v1 Announce Type: new Abstract: Agile and reliable navigation is a core capability for embodied robots navigating complex spatial constraints and dynamic interactions. However, a singl
arXiv:2610.13034v1 Announce Type: new Abstract: Trajectory extrapolation from a partial target trajectory is underdetermined, but completed related trajectories provide information about the unresolve
arXiv:2610.13895v1 Announce Type: cross Abstract: Large language models reuse the same attention heads across tasks, but identifying these shared heads does not explain what they do differently in eac
arXiv:2610.12921v1 Announce Type: new Abstract: Brain-computer interfaces decode neural activity, yet class-label supervision (CLS) leaves relationships among classes implicit. We propose Language as
arXiv:2606.19821v2 Announce Type: replace Abstract: Key Performance Measurement (KPM) forecasting is essential for proactive network management of 5G and next-generation telecom networks. However, exi
arXiv:2610.12874v1 Announce Type: new Abstract: Long-term memory has been widely adopted in LLM-based agents to support persistent interaction and personalized assistance. Long-term multi-party intera
arXiv:2610.13221v1 Announce Type: new Abstract: Cancer diagnosis and treatment increasingly rely on multi-modal diagnostic technologies that generate high-dimensional datasets. Although these datasets
arXiv:2406.07177v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable performance on Natural Language Processing (NLP) tasks, but they are hindered by high computat