Knowledge catalogue
arXiv:2610.13186v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training without exposing raw data, yet remains vulnerable to malicious clients injecting poisoned d
Hey r/LocalLLaMA! Maintainer here. Some of you might remember OpenMed from our 1.8 post a few months back. Quick recap: it's an open-source (Apache-2.0) medical AI toolkit with one rule we never break
https://preview.redd.it/uyjw2lcrvkuh1.png?width=1536&format=png&auto=webp&s=ce991be22faec3de5cbaf39119c14782b6ed0af3 link to article TLDR; new microsoft surface and nvidia rtx spark laptops are starti
arXiv:2610.11270v1 Announce Type: cross Abstract: Personalized conversational AI relies on long-term memory systems that extract facts from user utterances and store them in persistent vector stores.
arXiv:2610.11628v1 Announce Type: cross Abstract: Machine unlearning updates a trained model after records are deleted, aiming to match exact retraining without repeating the full training procedure.
TL;DR: For my use case, mradermacher/Signal-3.8-27B-Terse-Coder.i1-Q4_K_M proved out. Ymmv based on your domain-specific tests. Time taken to solve problems compared to frontier models is massive; esp
arXiv:2610.09424v1 Announce Type: cross Abstract: Deploying Mixture-of-Experts (MoE) models relies heavily on Expert Parallelism, which generates intense inter-GPU communication. Consequently, state-o
arXiv:2610.09304v1 Announce Type: cross Abstract: Facial movements convey subtle and important information that is critical for human social communication. Optical methods for face capture are difficu
arXiv:2610.09907v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong performance across a wide range of downstream vision tasks, thanks to the complementary information cont
arXiv:2512.08617v2 Announce Type: replace Abstract: This tutorial focused on Healthcare Domain Applications of NLP, what we have achieved around HealthcareNLP, and the challenges that lie ahead for th
The ASUS blog post (Oct 8 2026) announces a collaboration between ASUS, Hermes, and Nous Research to launch an accessible local‑first AI chatbot aimed at creative workflows. Designed for ProArt device
arXiv:2610.09209v1 Announce Type: new Abstract: Substance Use Disorder (SUD) counseling requires patient responses that reflect underlying cognitive states such as beliefs, coping strategies, and read
arXiv:2610.09981v1 Announce Type: cross Abstract: LLM routers pick a cheap or expensive model per request by its content, and many gateways and some cloud platforms can log that choice with content lo
arXiv:2610.09120v1 Announce Type: new Abstract: Randomized exploration is central to bandit learning, multi-agent reinforcement learning, and zeroth-order policy search, yet its independence and priva
Editor’s note: This article is adapted from Thomas Kurian’s keynote address at Gemini at Work 2026. It includes a number of announcements: Gemini, a single, universal agent for work that answers your
arXiv:2610.07602v1 Announce Type: cross Abstract: We develop a mesh-free neural JKO scheme for advection-reaction-diffusion equations with a gradient-flow structure in the Hellinger-Kantorovich (HK) g
arXiv:2610.07904v1 Announce Type: new Abstract: We introduce ApexQuant, a calibration-free quantization method that recursively re-quantizes the residual error, serving as a refinement layer on top of
arXiv:2610.05828v2 Announce Type: replace Abstract: Large language models (LLMs) offer new opportunities for public opinion research by enabling early prediction of survey responses, potentially reduc
arXiv:2610.08107v1 Announce Type: cross Abstract: Attacker ASV systems for voice anonymization have been studied primarily in English, leaving their behavior in multilingual settings largely unexplore
arXiv:2603.21276v2 Announce Type: replace-cross Abstract: The growing demand for on-device large language model (LLM) services on mobile edge devices has driven the adoption of Mixture-of-Experts (MoE
arXiv:2610.08093v1 Announce Type: cross Abstract: Developing reliable models for clinical tasks, such as Medical Question Answering (QA), is severely constrained by the limited availability of high-qu
arXiv:2610.04051v1 Announce Type: new Abstract: Accurate early screening for Autism Spectrum Disorder (ASD) is a precursor to timely intervention, which is critical for improving cognitive and behavio
arXiv:2610.06748v1 Announce Type: cross Abstract: In decentralized consumer-to-consumer (C2C) marketplaces, people list goods, negotiate with strangers, and rate one another, so trust rests on reputat
arXiv:2610.04526v1 Announce Type: cross Abstract: Disasters can overload cellular control-plane signaling within minutes, yet fine-grained Radio Resource Control (RRC) or Next Generation (NG) Applicat
arXiv:2610.04569v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in safety-critical settings, yet their black-box nature makes it difficult to provide formal gu
arXiv:2610.05102v1 Announce Type: new Abstract: We study differentially private learning problems in the realizable setting, where a hypothesis is specified by k components. A direct iteration of priv
arXiv:2610.06334v1 Announce Type: new Abstract: Diffusion models have greatly advanced instruction-guided image editing, while also raising concerns about unauthorized image manipulation. Image immuni
Octop is an open-source, self-hosted AI assistant. Through its multi-agent architecture, it builds an intelligent environment that is both independent and collaborative for teams, families, and indivi
arXiv:2610.03597v1 Announce Type: new Abstract: Federated learning lets many clients train a shared model together without ever sending their private data to a central server. Each client shares only
arXiv:2607.18257v2 Announce Type: replace-cross Abstract: When AI agents shift from answering questions to taking actions, users face a new problem: deciding what to delegate, to a system whose action
arXiv:2610.03330v1 Announce Type: cross Abstract: We consider a distributed learning task with agents that have correlated data. Specifically, the label of an agent depends on the input of other agent
arXiv:2610.02750v1 Announce Type: new Abstract: We address the Person Goal Navigation (PersonNav) problem, enabling robots to search for people under realistic constraints on information accessibility
arXiv:2610.02418v1 Announce Type: cross Abstract: Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible websit
arXiv:2610.02386v1 Announce Type: cross Abstract: We present a comprehensive overview of the challenges and opportunities in social bot detection in the context of the rise of sophisticated AI-based c
tl;dr: I created a fully-local open-source full-duplex voice agent that rivals GPT-Live on some benchmarks. It uses Voxtral Realtime with a turn-taking head, a microturn-finetuned Gemma 4 12B and Bree
arXiv:2610.02599v1 Announce Type: new Abstract: Sustainable protein discovery lacks the fast computational proxies, analogous to molecular docking or density functional theory, that accelerate drug an
arXiv:2610.03057v1 Announce Type: new Abstract: Relational foundation models are increasingly pretrained on synthetic databases, yet downstream benchmarks reveal little about why one synthetic corpus
Wired: Extracted system prompts show Meta's Muse compiles “a page for every person in the user's life”, with facts, history, tips to improve relationships, and more — Millions have downloaded Meta's A
From the first LLaMA 33B I knew I wanted that magic-like intelligence locally, mine, so nobody could take it away when I needed it. I bought a 3090 for my home PC. Then LLaMA 65B appeared and I was
Auto-generated synthesis of 29846 entries about arxiv-cs-ai
arXiv:2610.00069v1 Announce Type: cross Abstract: Long-horizon ego/exo data contains rich procedural evidence, but are redundant, noisy, and costly to process or retain. We propose a compact framework
arXiv:2610.01944v1 Announce Type: new Abstract: Few-shot personalization enables large vision--language models (LVLMs) to learn user-specific visual concepts for applications such as personalized retr
arXiv:2507.17389v2 Announce Type: replace-cross Abstract: Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these mod
Somebody just released a fully open-source, open-weights decision model that beats Jev! Just kidding, it's me and I this is my first time releasing a public model, recipe and dataset so I am looking f
arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook
arXiv:2610.01963v1 Announce Type: new Abstract: Emergency department (ED) triage is a high-stakes prioritization task in which demographic, socioeconomic, and system-context information may improperly
arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co
arXiv:2610.01510v1 Announce Type: new Abstract: Robust perception in intelligent vehicles demands 3D object detectors that remain dependable under domain shifts, such as changes in time of day, locati
arXiv:2610.00693v1 Announce Type: new Abstract: Federated learning (FL) has recently attracted increasing attention in remote sensing (RS) since it enables collaborative model training across decentra
arXiv:2610.01126v1 Announce Type: new Abstract: Federated learning (FL) is a communication-efficient distributed learning paradigm. However, client drift remains one of the most critical challenges, h
arXiv:2610.00382v1 Announce Type: cross Abstract: Model quantization reduces the numerical precision of neural network weights and activations to lower storage and computational costs. Model inversion
arXiv:2610.00284v1 Announce Type: cross Abstract: The partial area under the receiver operating characteristic curve (pAUC) is an important performance metric for binary classification that summarizes
arXiv:2610.01184v1 Announce Type: cross Abstract: Remote multimodal models offer strong numerical reasoning capabilities over charts and speech, but sending private inputs risks exposing sensitive con
arXiv:2610.01768v1 Announce Type: cross Abstract: With the increasing capabilities of Large-Language-Models (LLMs) and LLM-based agents, users are increasingly using them to solve everyday problems, s
arXiv:2610.01647v1 Announce Type: cross Abstract: In this article, we present our vision and recent advancements toward creating a decentralized system capable of learning from real-time data within b
Michael Shepard / Bloomberg: US authorities arrest a California man suspected of smuggling $300M+ worth of restricted Nvidia AI chips to China via Malaysia and Singapore from 2023 to 2024 — By continu
arXiv:2609.39537v1 Announce Type: cross Abstract: The EU AI Act (Art. 27) requires deployers of high-risk AI systems to conduct Fundamental Rights Impact Assessments (FRIAs) before deployment, yet the
arXiv:2609.34211v2 Announce Type: replace Abstract: In financial fraud detection, rich semantic context can provide important evidence for transaction behavior modeling and fraud reasoning. However, p
arXiv:2609.40236v1 Announce Type: new Abstract: Converting free-text radiology reports into structured labels supports cohort building, quality assurance, and monitoring of clinical imaging models, bu
arXiv:2601.22028v2 Announce Type: replace Abstract: Most LLM unlearning methods aim to approximate retrain-from-scratch behaviors with minimal distribution shift, often via alignment-style objectives