Knowledge catalogue
arXiv:2605.30335v1 Announce Type: new Abstract: Multi-component LLM agents assemble probabilistic claims from components that each see only part of a joint problem; the composition can violate basic p
arXiv:2603.27150v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized medical reasoning tasks, yet single-agent systems often falter on complex, interdisciplinary proble
arXiv:2605.30159v1 Announce Type: new Abstract: Memory-augmented LLM agents tackle complex long-horizon tasks by recursively summarizing interaction trajectories into compact memory. However, existing
arXiv:2605.29622v1 Announce Type: new Abstract: Coupled-cluster (CC) theory is often considered the gold standard of quantum chemistry, but its high computational cost limits routine access to accurat
arXiv:2601.05149v2 Announce Type: replace Abstract: Autoregressive (AR) models have achieved remarkable success in image synthesis, yet their sequential nature imposes significant latency constraints.
ComfyUI's MultiGPU feature, which allows users to distribute memory between VRAM and RAM effectively , has been integrated into the core ComfyUI codebase as native support. This enhancement enables CU
Liquid AI released LFM2.5-8B-A1B, a device-optimized model designed to power real-life applications on phones, laptops, PCs, robots, and lightweight server-side use-cases. The model is a fast, memory-
OpenJarvis: a local-first personal AI is now available to run with Ollama Built by Stanford’s @HazyResearch and Scaling Intelligence labs, as part of their “Intelligence Per Watt” research into effici
PlagueKind Nodes is a ComfyUI custom node designed to facilitate stacking multiple LTX LoRAs (Low-Rank Adaptations) within a single node, offering streamlined management for adding and removing these
arXiv:2605.29275v1 Announce Type: new Abstract: Open-ended post-training benefits from rewards that make prompt-specific success conditions explicit, rather than relying only on post-hoc scalar scores
arXiv:2605.29158v1 Announce Type: new Abstract: Protein homology search underlies function annotation, structure prediction, and evolutionary analysis, but remains challenging in the 'twilight zone,'
arXiv:2605.30075v1 Announce Type: new Abstract: Quantum Federated Learning (QFL) offers a promising framework to train quantum models across distributed clients while keeping data strictly local. Due
arXiv:2605.29538v1 Announce Type: new Abstract: With the emergence of wireless applications in three-dimensional environments, such as the low-altitude airspace and 3D heterogeneous networks, radio ma
arXiv:2605.30327v1 Announce Type: cross Abstract: Frontier reasoning models are produced by posttraining base language models with reinforcement learning. Recent work has challenged this by showing th
arXiv:2605.28831v1 Announce Type: cross Abstract: Long-horizon interactive agents often accumulate large trajectory histories yet still fail to answer questions about earlier events reliably. We argue
arXiv:2603.13249v2 Announce Type: replace-cross Abstract: Activation steering offers a computationally efficient mechanism for controlling Large Language Models (LLMs) without fine-tuning. While effec
arXiv:2605.29826v1 Announce Type: cross Abstract: Existing methods in Multimodal Knowledge Editing (MKE) have advanced the ability to correct outdated or inaccurate knowledge in Multimodal Large Langu
arXiv:2509.24895v2 Announce Type: replace Abstract: While protein language models (PLMs) are one of the most promising avenues of research for future de novo protein design, the way in which they tran
arXiv:2605.29534v1 Announce Type: new Abstract: Recent advances in mobile GUI agents have shown strong potential for automating mobile tasks, but most effective systems still depend on large vision-la
arXiv:2605.30227v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) empower Large Language Models to tackle complex reasoning tasks through collaborative interaction, optimizing their dy
arXiv:2605.29287v1 Announce Type: cross Abstract: Item-to-Item (I2I) retrieval is a fundamental part of modern content platforms, supporting critical industrial workflows from recommendation engines t
arXiv:2605.29691v1 Announce Type: new Abstract: Self-supervised learning (SSL) has produced a diverse landscape of vision transformers (ViTs) whose pretrained representations support a wide range of d
An updated MarkItDown API Server integrates Microsoft MarkItDown for converting PDF files, images, and Word documents to Markdown, with Ollama and LLaVA for generating image descriptions. This project
This discussion likely covers methods and tools for combining or merging multiple video files generated with Stable Diffusion, an AI image and video generation model. Community members likely share re
Web Chat para Ollama is a tool that enables users to run a private, free AI chat interface locally on their own machines using Ollama, an open-source framework for running large language models. The p
arXiv:2605.30102v1 Announce Type: cross Abstract: The design space of agentic AI inference spans two extremes: frontier large language models (LLMs), typically hosted in the cloud and offering strong
arXiv:2605.28578v1 Announce Type: new Abstract: We propose the Tikhonov layer, a graph neural network layer that is interpretable by design: once trained, its learned parameters directly reveal which
arXiv:2605.27763v1 Announce Type: new Abstract: Safety evaluations of language models often treat serving configuration as fixed background infrastructure, but batch condition is an untested treatment
arXiv:2511.02398v2 Announce Type: replace Abstract: We present a novel decentralized algorithm for coverage control in unknown spatial environments modeled by Gaussian Processes (GPs). To trade-off be
This post announces an 8-9 billion parameter language model optimized for efficiency and speed, trained on a very large token dataset, and positioned as accessible for users with limited GPU resources
arXiv:2605.28362v1 Announce Type: new Abstract: Mobile robot path planning methods are often constrained by vast search spaces, resulting in latency in samplingbased algorithms. Learning-based approac
arXiv:2605.27986v1 Announce Type: new Abstract: Messenger RNA (mRNA) sequences as therapeutics require optimized design to ensure efficient translation, structural stability, and minimal immunogenicit
Wall Street Journal: As Google plans to build a $15B AI data center hub in India's Visakhapatnam, locals and rights groups are raising concerns over “extremely high” water stress — Developing-world na
b9374 is a release of llama.cpp from May 28, 2026 , focused on continuous integration improvements. The release includes refactoring of CI/CD workflows, separate CUDA Windows workflow configuration, c
b9375 is a release of llama.cpp, a project for LLM inference in C/C++. The release likely contains bug fixes, performance improvements, or feature additions to the llama.cpp codebase. Specific details
Based on the available information about llama.cpp, b9378 is likely an intermediate build release of the llama.cpp project. llama.cpp enables LLM inference in C/C++ , and the project releases multiple
B9381 is a build/release tag for llama.cpp, a C/C++ framework for LLM inference. This release likely includes bug fixes, performance optimizations, and feature improvements to the project, which enabl
I don't have specific information about release b9382 from llama.cpp. Based on the GitHub release tag format, this entry likely documents a specific build or commit version of llama.cpp, which is a C+
arXiv:2605.27674v1 Announce Type: cross Abstract: Cyber-Physical Systems (CPS) integrate sensing, communication, computation, and control to support critical infrastructure, including smart grids, ind
arXiv:2605.28729v1 Announce Type: cross Abstract: Robustness of neural networks is commonly quantified via local or global Lipschitz constants. However, Lipschitz continuity can be overly coarse or ov
arXiv:2605.28115v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods the
arXiv:2605.28387v1 Announce Type: cross Abstract: Recognizing and continuously learning novel human actions without forgetting prior classes is a requirement for emerging AR/VR and robotics applicatio
arXiv:2605.28521v1 Announce Type: new Abstract: ClinicalEncoder26AM is a multilingual Diagnosable ColBERT for clinical and biomedical texts, which aligns at multiple levels its token-level semantic wi
Create transformation videos where a cube, sphere, capsule, or custom object transforms into a person or item with a button press using Seedance 2.0 inside ComfyUI. The workflow automatically generate
arXiv:2602.03491v2 Announce Type: replace-cross Abstract: Reasoning over table images remains challenging for Large Vision-Language Models (LVLMs) due to complex layouts and tightly coupled structure-
arXiv:2507.22554v3 Announce Type: replace Abstract: To understand our global progress for sustainable development and disaster risk reduction in many developing economies, two recent major initiatives
arXiv:2605.28018v1 Announce Type: new Abstract: Given the real-time demands of UAV tracking, many methods simplify the backbone to reduce computation, but this often weakens feature representation and
arXiv:2605.27432v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) has emerged as a paradigm for grounding large language models in external knowledge, yet most existing RAG system
arXiv:2605.28200v1 Announce Type: new Abstract: Single-cell RNA sequencing (scRNA-seq) profiles large numbers of cells but loses spatial context, whereas spatial transcriptomics (ST) preserves partial
arXiv:2605.28811v1 Announce Type: new Abstract: We present a method for harmonizing the lighting of a foreground video to match a target background scene, adjusting shadows, color tone, and illuminati
arXiv:2605.27489v1 Announce Type: cross Abstract: Multi-agent LLM systems decompose workflows across agents, tools, shared context, memory, and decision gates. This modularity improves interpretabilit
A Chrome extension built for automated web interaction and data extraction that uses Ollama's local LLM capabilities to intelligently navigate websites, scroll pages, fill out forms, type text, and sc
arXiv:2605.28320v1 Announce Type: cross Abstract: This paper addresses the problem of identifying parsimonious explicit piece-wise polynomial relationships that might involve a relatively large number
arXiv:2603.16985v2 Announce Type: replace Abstract: Transformer-based models have been widely adopted for time-series forecasting due to their high representational capacity and architectural flexibil
arXiv:2605.27786v1 Announce Type: cross Abstract: Large language models are known to contain representational redundancy across network depth, making depth pruning an effective approach for improving
arXiv:2605.28170v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly integrated into high-stakes decision-making, the ability to reliably quantify uncertainty has become a
arXiv:2605.27937v1 Announce Type: cross Abstract: Scintillation detectors with excellent timing resolution enable more precise localization of radiation sources in positron emission tomography, leadin
arXiv:2502.17832v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has become a common practice in multimodal large language models (MLLM) to enhance factual grounding and
arXiv:2602.12843v2 Announce Type: replace Abstract: Chest X-ray (CXR) reporting follows a region-based clinical workflow in which radiologists inspect anatomical regions and integrate localized findin
arXiv:2605.28805v1 Announce Type: cross Abstract: Visual outcomes are increasingly central to multimodal large language models, making reliable and fine-grained verification essential for scaling gene