Knowledge catalogue
arXiv:2609.27334v1 Announce Type: new Abstract: Agentic memory systems reuse past experience to improve future performance, yet most existing designs curate memory at write time: once a task is comple
Just trained Tev1 0.8B, a tiny Jev-like classifier. Here it is running completely locally on my mac with @ollama & classifying some tasks. It's extremely fast: only ~50ms E2E latency. Video is not spe
arXiv:2609.27467v1 Announce Type: cross Abstract: Long-term autonomy in human-populated environments requires anticipating whether and how people will move at times a robot has not yet observed. Exist
arXiv:2609.27216v1 Announce Type: cross Abstract: Topology optimization (TO) remains computationally intensive due to repeated finite element analysis (FEA) evaluations required at each iteration. Whi
arXiv:2609.27294v1 Announce Type: cross Abstract: Scaling a language model is not only a question of final quality: the architectural choice determines how much computation is spent during training, p
arXiv:2609.27509v1 Announce Type: new Abstract: Stereo visual SLAM systems built on local descriptors suffer from semantic ambiguity, instance-level confusion, and independently moving objects, each c
German artificial intelligence security startup Kontext today announced 4 million in new funding for software that controls what AI agents are allowed to do once they are running inside a business. Ko
arXiv:2609.27814v1 Announce Type: cross Abstract: In statutory question answering, every claim must be traceable to evidence, not merely relevant, since unverifiable labour-rights answers carry seriou
arXiv:2609.27297v1 Announce Type: new Abstract: Accumulated scientific knowledge advances inquiry when prior findings help researchers choose new questions, design investigations, and interpret result
arXiv:2609.28225v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) operating in GNSS-denied urban environments require alternative methods for position estimation. Existing approaches bas
arXiv:2609.27006v1 Announce Type: cross Abstract: We present a laser-tracker-assisted hand-eye calibration method for camera-equipped mobile robots. The method combines laser-tracker-based 3D metrolog
arXiv:2609.27455v1 Announce Type: new Abstract: World Action Models (WAMs) jointly model action generation and environment dynamics and are mostly built on pretrained Video Diffusion Models (VDMs). In
arXiv:2609.28086v1 Announce Type: cross Abstract: We propose LAYERSCOPE, a label-free, layerwise framework that aims to characterize a model's learned representations in video and multimodal settings.
arXiv:2609.28364v1 Announce Type: cross Abstract: Control barrier functions (CBF) are a popular safety filter to ensure safety for nonlinear dynamical systems. However, when the system is subject to u
arXiv:2609.27307v1 Announce Type: new Abstract: Graphical User Interface (GUI) agents enable the fulfillment of complex user instructions through multi-turn interactions with software environments, re
arXiv:2609.28027v1 Announce Type: new Abstract: Providing personalized exoskeleton assistance across varying walking speeds remains challenging. Existing online optimization methods are sample-ineffic
arXiv:2609.28405v1 Announce Type: new Abstract: Collective responses depend on individual differences, contact opportunities, and accumulated experience. Learning their dynamics from aggregate counts
arXiv:2609.27188v1 Announce Type: new Abstract: Dissipativity is a fundamental system-theoretic property closely related to stability, passivity, and input--output stability, and is particularly impor
arXiv:2609.27003v1 Announce Type: new Abstract: Runway walking requires coordinated control of posture, stride, foot placement, and whole-body motion to effectively present clothing and convey a disti
arXiv:2609.28003v1 Announce Type: new Abstract: Small and medium-sized language models offer cost-effective executors for tool-using agents, making them attractive for local and large-scale deployment
arXiv:2609.28409v1 Announce Type: cross Abstract: Vector Symbolic Algebras project data structures into a hyperdimensional vector space through the application of their vector algebras to randomly gen
arXiv:2609.27637v1 Announce Type: cross Abstract: Traffic flow forecasting is essential to intelligent transportation systems. Large-scale traffic forecasting requires jointly modeling local spatial d
arXiv:2609.27144v1 Announce Type: new Abstract: We consider the problem of learning risk scores to prioritize individuals for scarce resources or interventions, from historical observational data affe
arXiv:2609.27217v1 Announce Type: cross Abstract: We address adaptive computation in 3D medical image segmentation: instead of designing another backbone, we ask how much spectral mixing each network
arXiv:2609.26816v1 Announce Type: cross Abstract: This paper develops a data-driven framework for long-term prediction of fluid--structure interaction (FSI) dynamics, focusing on the flow-induced vibr
arXiv:2609.28322v1 Announce Type: new Abstract: Benchmarking and routing platforms increasingly act as intermediaries connecting large language model providers with end-users. However, providers on th
arXiv:2609.27764v1 Announce Type: new Abstract: We treat options pricing as a representation problem: can machine learning detect systematic deviations from Black-Scholes using 2.6M real option contra
arXiv:2603.28790v2 Announce Type: replace-cross Abstract: In edge computing, the stochastic and bursty nature of serverless workloads challenges autonomous resource orchestration. Traditional reactive
arXiv:2609.27869v1 Announce Type: new Abstract: Long-horizon multimodal agents rely on specialized capabilities for perception, retrieval, reasoning, verification, and execution. Existing designs typi
arXiv:2609.27925v1 Announce Type: new Abstract: Language models can over-condition on irrelevant preceding text: predictions already supported by local context may still change when distant, unrelated
arXiv:2609.27473v1 Announce Type: new Abstract: PPG-to-vital-sign reconstruction turns a wrist-worn photoplethysmogram into clinical waveforms such as the ECG. Long-horizon multivariate time-series fo
arXiv:2609.27009v1 Announce Type: new Abstract: Large language models are increasingly applied to high-risk domains such as law, yet complex legal reasoning remains limited by two structural challenge
arXiv:2602.17818v2 Announce Type: replace Abstract: Speech enhancement performance degrades significantly in noisy environments, limiting the deployment of speech-controlled technologies in industrial
arXiv:2609.27747v1 Announce Type: cross Abstract: Vision-language-action models (VLA) promise human-steerable autonomous driving, but their training is bottlenecked by the scarcity of frames paired wi
arXiv:2609.26981v1 Announce Type: new Abstract: We describe deploying imaging AI at six hospitals through PACS-AI, an open self-hosted platform. The binding constraint is not model accuracy but infras
arXiv:2609.27032v1 Announce Type: new Abstract: Faithfulness is a central concern in legal text summarization, which motivates extractive approaches that select verbatim content traceable to its sourc
arXiv:2609.28078v1 Announce Type: new Abstract: Segmentation-based multi-object tracking (MOT) with foundation video models such as SAM2 offers strong localization quality, yet remains fragile in crow
arXiv:2609.28327v1 Announce Type: new Abstract: We present LightMIS, a scalable family of ultra-lightweight convolutional networks for 2D binary medical image segmentation without a learned stage-wise
arXiv:2609.28431v1 Announce Type: new Abstract: Dexterous manipulation demands long-term foresight and rapid reactive control. Vision-Language-Action (VLA) models, while proficient in high-level reaso
arXiv:2609.27741v1 Announce Type: new Abstract: In value-based reinforcement learning, improving the accuracy of policy evaluation has been shown to improve downstream policy optimization performance.
arXiv:2609.27964v1 Announce Type: new Abstract: Empirical scaling laws for autoregressive language models relate prediction loss to model size, data size, and optimization compute, but their theoretic
arXiv:2609.27246v1 Announce Type: cross Abstract: As embodied agents take on increasingly social and relational roles in VR, visual realism and embodiment alone may be insufficient; users must also pe
arXiv:2609.27303v1 Announce Type: new Abstract: Livestreams are long-lasting interactive environments where audiovisual content, viewer activity, host behavior, and platform signals evolve together, c
arXiv:2402.17937v2 Announce Type: replace Abstract: Mental health is a significant healthcare challenge, and cognitive behavioral therapy (CBT) is a widely used therapeutic method for treating anxiety
I’ve been experimenting with local AI lately, and one thing I’m finding interesting is what comes after getting a model running. Ollama makes local model access pretty straightforward, but for an actu
arXiv:2609.27092v1 Announce Type: cross Abstract: Many node-classification GNNs apply a linear classifier to a nonnegative mixture of local messages. An error can reflect either poor mixture weights o
arXiv:2609.28338v1 Announce Type: cross Abstract: Local geometric mixing localizes geometric mixing by requiring geometric convergence to equilibrium in total variation only over finitely many transit
arXiv:2609.27959v1 Announce Type: cross Abstract: We investigate a local spectral-complexity representation for perceptual image quality assessment (IQA) based on Shannon entropy of singular values co
arXiv:2505.04417v3 Announce Type: replace Abstract: Diffusion models are state-of-the-art tools for various generative tasks. Yet training these models involves estimating high-dimensional score funct
arXiv:2609.27220v1 Announce Type: new Abstract: Diffusion language models generate text through iterative denoising, exposing intermediate trajectories before final answers are produced. We identify a
arXiv:2609.28212v1 Announce Type: cross Abstract: Language modeling using Transformers has become commonplace despite their fixed computational depth and quadratic runtime with respect to input tokens
arXiv:2603.16932v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) typically process images at a native high-resolution, forcing a trade-off between accuracy and computational eff
arXiv:2609.27024v1 Announce Type: cross Abstract: Volatility forecasts play a central role in financial risk management because their overall level and day-to-day movements affect downstream decisions
arXiv:2608.24707v2 Announce Type: replace Abstract: While text-based hallucination detection is well studied, reference-free detection of factual alterations in speech remains underexplored, especiall
arXiv:2609.26839v1 Announce Type: cross Abstract: Post-hoc probability calibration is usually evaluated under an optimistic assumption: the held-out calibration labels are clean. In many AI deployment
LWiAI Podcast #257 (recorded 19 Sep 2026) reviewed OpenAI’s latest model, GPT‑6 Astra, noting its agentic coding focus and purported loop‑transformer reasoning as a significant capability jump. The ep
arXiv:2609.27523v1 Announce Type: new Abstract: Breast image classification requires local detail and global tissue context, yet these cues can weaken as representations deepen. We present M3D-Net, a
I'm about to buy a Mac Studio mainly for running LLMs locally and I'm stuck between two configs: M5 Ultra (30/64) with 96GB: 1.2 TB/s bandwidth, roughly 1.7x faster generation and much faster prefill
Hello Everyone! Good news for anyone who can compile code on apple, you can now experience using a AMD Radeon AI Pro R9700 on a MacBook Pro or Mac mini, Mac Studio or any OSX variant as long as it has
arXiv:2609.26866v1 Announce Type: new Abstract: Tool-result caching reduces repeated execution in agent training, but also couples rollout randomness. We study a two-action model in which independent