Knowledge catalogue
arXiv:2609.38637v1 Announce Type: cross Abstract: Visual object tracking typically assumes that the initial template and subsequent search frames share the same sensing modality. In practice, sensor a
arXiv:2609.38574v1 Announce Type: new Abstract: Large language models are frequently proposed as a route to AI-powered services for African communities, but they are least reliable exactly where the n
arXiv:2609.39247v1 Announce Type: cross Abstract: Standard language model RL algorithms credit every token of a long rollout with the same advantage determined by the terminal reward. Actor-critic met
arXiv:2609.39684v1 Announce Type: new Abstract: Privacy has become an increasingly important concern in the Document Analysis community, to the extent that in many environments such as archives, gover
arXiv:2609.39464v1 Announce Type: new Abstract: In federated averaging, local objectives can admit multiple optimal heads, making the aggregate depend on which heads clients return. We study this ambi
arXiv:2607.18446v2 Announce Type: replace Abstract: Purpose: Understanding how much of routine policing involves vulnerable people could inform resourcing, training, and multi-agency response, yet adm
arXiv:2609.38270v1 Announce Type: cross Abstract: Advancing beyond traditional static scoring models, LLM-powered agentic recommender systems (LLM-ARS) instantiate users and items as autonomous agents
arXiv:2609.40129v1 Announce Type: new Abstract: Reasoning through video generation offers a promising path toward visual intelligence by modeling latent visual states and their dynamics. However, curr
arXiv:2609.39989v1 Announce Type: new Abstract: Background. A component replacement in a language-model agent changes an execution trajectory, potentially altering later observations, resource use, an
3 models are now available on Ollama for use with /v1/systemone: • Nimble: https://ollama.com/library/nimble • Tev1 4b: https://ollama.com/library/tev1:4b • Tev1 0.8b: https://ollama.com/library/tev1:
arXiv:2609.36079v1 Announce Type: new Abstract: When a doctor, a judge, or an engineer must decide whether to trust an AI model's output, they cannot avoid asking what the model understands. Purely ma
arXiv:2609.37184v1 Announce Type: new Abstract: Dynamic simulations are an entrenched way of gaining insight into the evolution of system dynamics. Their computational cost however is often prohibitiv
arXiv:2609.37200v1 Announce Type: new Abstract: Multi-reward guided reinforcement learning (i.e., RL) offers a promising way to improve joint audio-video diffusion models along several complementary o
After a brief period where OpenAI seemed to be unifying work around the ChatGPT app, between Dot and Spaces and Pages and local/cloud ChatGPT Work and Scheduled Tasks in the Cloud and Scheduled Tasks
arXiv:2609.37285v1 Announce Type: new Abstract: Laboratories often face a new molecular assay with 16-64 labels and a bank of predictors whose training data and parameters are unavailable. The practic
arXiv:2609.36722v1 Announce Type: new Abstract: Large language model (LLM) agents repeatedly load reusable content, such as skills, documents, and memory entries, into the current context. Re-encoding
arXiv:2609.36662v1 Announce Type: cross Abstract: The pre-training of Large Language Models (LLMs) is increasingly conducted across multiple data centers. As training scales to a larger number of acce
arXiv:2609.36503v1 Announce Type: new Abstract: Adding or removing a sounding object requires coordinated changes to visual content and sound while preserving the surrounding scene. Yet paired supervi
arXiv:2609.37644v1 Announce Type: new Abstract: Latent world models often struggle with long-horizon planning despite accurate short-term predictions. Recursive rollouts accumulate errors, while dista
**Ollama Blog – “Ollama Now Supports JEW‑Style Decision Models” (Sep 30 2026).** The post announces that Ollama now includes native support for JEW‑style decision models, expanding its generative AI c
arXiv:2609.36965v1 Announce Type: new Abstract: System One models such as Jev offer an efficient alternative to generative language models for tasks that require decisions rather than open-ended respo
arXiv:2609.37721v1 Announce Type: cross Abstract: Robot policies increasingly incorporate semantic reasoning and future-world prediction, yet combining these capabilities does not guarantee that local
arXiv:2609.34240v2 Announce Type: replace-cross Abstract: Existing open-ended generation metrics measure likelihood, lexical diversity, or distributional similarity in generic representation space, ye
arXiv:2609.37260v1 Announce Type: new Abstract: Object-centric scene reconstruction requires completing partial object observations while preserving metric alignment and avoiding collisions with the s
Tasks where an MLLM doesn't write text but only makes a decision, which started with Jev, seem to be getting popular. (This is sometimes called 'typed decision'.) I thought it would be fun to use insi
arXiv:2609.36928v1 Announce Type: new Abstract: Training robot manipulation policies relies on costly robot demonstrations, making large-scale data collection impractical. Meanwhile, to improve policy
arXiv:2609.37458v1 Announce Type: new Abstract: Industrial standards often encode the same engineering concept through incompatible hierarchies, identifiers, roles, and structural constraints, so the
arXiv:2609.36616v1 Announce Type: new Abstract: Historical street-view imagery records urban evolution, but uneven coverage leaves substantial gaps in historical records. Generating plausible past app
arXiv:2605.06240v2 Announce Type: replace-cross Abstract: Forward-Forward (FF) training lets each layer learn from a local goodness criterion. In cumulative-goodness variants, later layers can inherit
arXiv:2509.06154v3 Announce Type: replace Abstract: Developing accurate, data-efficient surrogate models is central to advancing AI for Science. Neural operators (NOs), which approximate mappings betw
arXiv:2609.36324v1 Announce Type: cross Abstract: Flow-matching text-to-speech (TTS) models achieve high synthesis quality but require many neural function evaluations (NFEs) to integrate their genera
arXiv:2609.36504v1 Announce Type: new Abstract: Accurate prediction of three-dimensional (3D) microstructure evolution remains computationally demanding because high-fidelity phase-field simulations r
arXiv:2609.36770v1 Announce Type: new Abstract: Can a population of neural networks develop a useful division of labor without a shared gate or gradients between agents? We study a setting where each
arXiv:2609.37582v1 Announce Type: cross Abstract: Federated knowledge must remain usable by recipients with different modalities, private architectures, and tasks. We present FedSocket, which makes re
arXiv:2609.36560v1 Announce Type: cross Abstract: Object re-identification (ReID) faces a recurring challenge: different identities can share highly similar global appearances, while the cues that dis
arXiv:2609.36651v1 Announce Type: cross Abstract: Long-context reasoning in large language models incurs substantial computation and memory costs. Visual text compression (VTC) reduces input length by
Running things locally already means you care more about control and reproducibility than most. Worth extending that to your prompts too. There's a live workshop on Oct 3 covering exactly that. Serj S
arXiv:2602.08059v2 Announce Type: replace-cross Abstract: Text-to-image diffusion models can reproduce specific artists visual styles at extremely low cost, raising copyright and deployment safety con
arXiv:2609.36277v1 Announce Type: new Abstract: Existing protein geometry models typically represent molecular surfaces using local geometric features such as sampled points, normals, and curvature. W
arXiv:2609.36056v1 Announce Type: new Abstract: In urban low-altitude flight, buildings reshape ambient wind into spatially varying 3D flow, making unmanned aerial vehicle (UAV) energy depend on local
arXiv:2609.37042v1 Announce Type: new Abstract: Video Large Language Models (VideoLLMs) have achieved strong video understanding capabilities but incur substantial inference overhead due to the large
arXiv:2609.36477v1 Announce Type: cross Abstract: Guard models are used as safety classifiers, with confidence scores driving downstream moderation decisions. We evaluate five guard models for prompt
arXiv:2609.38006v1 Announce Type: new Abstract: Running a language model locally offers advantages in privacy, latency, and cost, but local hardware fits only small models, which are less capable than
The user expresses enthusiasm for the decision‑modeling approach introduced by @typesafeai’s JEV tool, emphasizing a preference for local deployment to protect sensitive data. After learning that @oll
arXiv:2609.36451v1 Announce Type: cross Abstract: Large language models often preserve meaning despite substantial changes in wording, style, and syntax, while small semantic edits can systematically
arXiv:2609.37988v1 Announce Type: new Abstract: As the context size of text processed with an LLM grows, the size of KV caches can outstrip the memory allocated for the original model weights. This im
arXiv:2609.35848v1 Announce Type: new Abstract: On-board compression of synthetic aperture radar (SAR) phase history is bandwidth-critical, and block-adaptive quantization (BAQ) remains the operationa
arXiv:2609.36882v1 Announce Type: new Abstract: Localizing AI-edited regions is essential for interpretable forensic analysis, but remains challenging due to subtle and spatially distributed artifacts
arXiv:2609.37937v1 Announce Type: new Abstract: How much of an image does a detector need to see? Small RGB regions can retain useful evidence of image synthesis even when they reveal little of the fu
arXiv:2609.37255v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are pretrained on heterogeneous collections containing billions of observations, yet their training windows are
arXiv:2609.38090v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are a compelling architecture for scaling model capacity, making them especially attractive for deployment on resource-c
arXiv:2506.01004v3 Announce Type: replace-cross Abstract: Unlike traditional video editing or inpainting, video semantic mixing fuses a reference concept with a moving target entity to produce a hybri
Hola a todos! Tengo un MacBook Pro m3 con 16gb de RAM. No me siento cómodo con los modelos que he probado y me gustaría saber qué modelo os sentís cómodo y para que lo usáis Muchas gracias! submitted
arXiv:2609.37387v1 Announce Type: new Abstract: Enlarged perivascular spaces (PVS) visible in brain magnetic resonance imaging (MRI) are increasingly thought to be linked to poor brain health. PVS are
arXiv:2609.37793v1 Announce Type: new Abstract: World-Action Models (WAMs) couple visual dynamics with action prediction, bringing the rich priors of pretrained video models to robotic manipulation. H
arXiv:2609.38098v1 Announce Type: new Abstract: Current vision-language models (VLMs) encode visual information in dense hidden states where object identity, spatial layout, and local attributes are i
I've been struggling with the ollama update process. I have both nvidia and amd GPUs in my system. I have two instances of ollama running on different ports for this to work around issues. AMD 7800xt
Ollama now supports Jev-like decision models all locally. Use decision models like Nimble for tasks like ticket triaging, model routing, and content moderation. ollama pull nimble Here’s Nimble playin
Hakan Gecili (@HakanGecili2) reported testing the AI models Tev1, Nimble, and Laya within his Pacman‑Arena game environment. The source code for this setup is available on GitHub at https://github.com
arXiv:2609.36838v1 Announce Type: cross Abstract: Visual agents solve problems by interleaving reasoning with image operations, and on-policy distillation (OPD) provides guidance from a strong teacher