Local LLM - privacy first - doctor
A discussion from the r/ollama community about using local large language models for privacy-sensitive applications, particularly for handling sensitive documents like medical records. Local LLMs proc
Knowledge catalogue
A discussion from the r/ollama community about using local large language models for privacy-sensitive applications, particularly for handling sensitive documents like medical records. Local LLMs proc
arXiv:2603.16284v2 Announce Type: replace Abstract: Despite the significant advancements in Large Vision-Language Models (LVLMs), their tendency to generate hallucinations undermines reliability and r
The post discusses a color shifting issue observed when using LTX model in Stable Diffusion, where generated images exhibit unwanted color variations or drift during processing. Community members like
arXiv:2512.05958v2 Announce Type: replace-cross Abstract: Generative search engines based on large language models (LLMs) are replacing traditional search, fundamentally changing how information provi
arXiv:2605.20043v1 Announce Type: new Abstract: We present an orthography-aware error analysis of Japanese past-tense morphological inflection, treating hiragana not merely as a transcriptional medium
arXiv:2605.19194v1 Announce Type: new Abstract: The Mixture-of-Agents (MoA) framework has shown promise in improving large language model (LLM) performance by aggregating outputs from multiple agents.
arXiv:2605.18869v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong performance across a wide range of tasks but are highly sensitive to prompt design, motivating the need fo
arXiv:2605.18870v1 Announce Type: new Abstract: In recent years, transformer architectures have revolutionized the field of language processing, opening the door to previously unforeseen possibilities
arXiv:2404.16676v2 Announce Type: replace-cross Abstract: We establish Multilayer Correlation Clustering, a novel generalization of Correlation Clustering to the multilayer setting. In this model, we
If you’re building visual shopping, image or document understanding, or chart analysis, you need a way to verify whether your model’s response is actually grounded in the source image. A text-only eva
arXiv:2605.18930v1 Announce Type: cross Abstract: Memory-augmented large language model (LLM) agents use iterative reflection and self-evolution to solve complex tasks, but these mechanisms introduce
arXiv:2605.19201v1 Announce Type: cross Abstract: Deep learning models detect pneumonia from chest X-rays with high accuracy, but the performance declines under domain shifts caused by differences in
arXiv:2512.01152v4 Announce Type: replace-cross Abstract: As we deploy machine learning systems in the real world, a core challenge is to maintain a model that is performant even as the data shifts. S
arXiv:2605.19351v1 Announce Type: cross Abstract: Generative agents based on large language models reproduce believable human behavior in cooperative settings, but how they should reason in situations
arXiv:2605.19932v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over long and recurring external contexts, like document corpora and code repositories. Across in
arXiv:2508.06526v3 Announce Type: replace-cross Abstract: As large-scale language models continue to scale up in both size and context length, the memory and communication cost of key-value (KV) cache
arXiv:2605.19685v1 Announce Type: cross Abstract: Accurately assessing financial risk requires capturing both individual asset volatility and the complex, asymmetric dependence structures that emerge
arXiv:2605.20079v1 Announce Type: cross Abstract: Diffusion and flow-based generative models dominate visual synthesis, with guidance aligning samples to user input and improving perceptual quality. H
arXiv:2605.20072v1 Announce Type: new Abstract: Large Language Models are increasingly proposed as cognitive components for robotic systems, yet their opaque decision processes make it difficult to ex
arXiv:2605.18799v1 Announce Type: cross Abstract: Large language models can fail in critic interaction not only by answering incorrectly, but also by abandoning an initially correct scientific solutio
arXiv:2605.18852v1 Announce Type: cross Abstract: Checkpoint selection for multimodal large language models (MLLMs) presents significant challenges when performance differentials are marginal and eval
arXiv:2605.19524v1 Announce Type: cross Abstract: End-to-end autonomous driving systems excel in common scenarios but struggle with safety-critical long-tail cases. Vision-Language-Action (VLA) models
arXiv:2605.19554v1 Announce Type: new Abstract: Instilling creativity in text-to-image (T2I) generation presents a significant challenge, as it requires synthesized images to exhibit not only visual n
arXiv:2505.17726v3 Announce Type: replace-cross Abstract: Recently, multimodal large language models (MLLMs) have emerged as a key approach in achieving artificial general intelligence. In particular,
arXiv:2605.20035v1 Announce Type: new Abstract: Omni-modal large language models (om-LLMs) achieve unified audio-visual understanding by encoding video and audio into temporally aligned token sequence
arXiv:2605.18851v1 Announce Type: new Abstract: Recent advances in Reinforcement Learning (RL) have underscored its potential for incentivizing reasoning capabilities of Large Language Models (LLMs).
arXiv:2605.19876v1 Announce Type: new Abstract: Text-to-3D generation based on diffusion models often suffers from the Janus problem, leading to inconsistent geometry across viewpoints. This work iden
arXiv:2605.18784v1 Announce Type: cross Abstract: The rapid diffusion of agentic AI has created a new coverage problem for commercial insurance: some AI-mediated losses are now affirmatively insured,
arXiv:2605.19561v1 Announce Type: cross Abstract: As Large Language Models (LLMs) advance toward practical deployment, the Microscaling FP4 (MXFP4) format has emerged as a cornerstone for next-generat
arXiv:2512.18552v2 Announce Type: replace-cross Abstract: While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivit
arXiv:2605.20055v1 Announce Type: cross Abstract: Explicit software architecture models are essential artifacts for communicating, analyzing, and evolving complex software-intensive systems. In ROS~2-
arXiv:2605.19539v1 Announce Type: new Abstract: Geometric foundation models hold promise for unconstrained dense geometry prediction from uncalibrated images. However, in current feed-forward designs,
arXiv:2605.19035v1 Announce Type: new Abstract: The rapid advancement of Large Language Models has given rise to autonomous LLM-based agents capable of complex reasoning and execution. As these agents
arXiv:2602.11767v3 Announce Type: replace Abstract: Advances in large language models (LLMs) are driving a shift toward using reinforcement learning (RL) to train agents from iterative, multi-turn int
arXiv:2605.19692v1 Announce Type: new Abstract: The microscopic examination of white blood cells (WBCs) plays a fundamental role in pathology and is essential for diagnosing blood disorders such as le
LetsEnhance with its Digital Art model is considered best for quality, delivering sharp lines and clearest eye detail with the highest output resolution ceiling. For a free desktop option, Upscayl off
arXiv:2605.19762v1 Announce Type: new Abstract: Code has become a standard component of modern foundation language model (LM) training, yet its role beyond programming remains unclear. We revisit the
arXiv:2605.19425v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become the dominant paradigm for advanced reasoning in Large Language Models (LLMs), but rol
This guide provides Chief Financial Officers with strategies for financial management and performance optimization in value-based care models, which shift healthcare reimbursement from volume-based to
arXiv:2605.16383v1 Announce Type: cross Abstract: Deep neural networks achieve high accuracy on image classification tasks. Yet, they often produce overconfident predictions as which fail to express e
arXiv:2605.17809v1 Announce Type: new Abstract: This research addresses the challenges inherent in developing Artificial Intelligence (AI) applications, particularly those leveraging Large Language Mo
arXiv:2510.04309v3 Announce Type: replace Abstract: Controlling the behaviors of large language models (LLM) is fundamental to their safety alignment and reliable deployment. However, existing steerin
arXiv:2605.16419v1 Announce Type: cross Abstract: Kinematic monitoring plays a critical role in long-term rehabilitation for patients with spinal cord injury (SCI), where multi-view markerless motion
This article from Latent Space provides guidance on securing employment at cutting-edge AI research laboratories, with a focus on roles related to pretraining large language models. It likely covers p
arXiv:2511.06316v3 Announce Type: replace Abstract: In low- and middle-income countries, public safety and urban planning initiatives frequently face a critical shortage of accurate, location-specific
arXiv:2605.17352v1 Announce Type: new Abstract: Despite substantial advances in large language models (LLMs), generating factually consistent responses for knowledge-intensive question answering remai
arXiv:2605.18529v1 Announce Type: new Abstract: The alignment of Large Language Models (LLMs) for complex reasoning heavily relies on Reinforcement Learning with Verifiable Rewards (RLVR). However, st
arXiv:2509.06503v2 Announce Type: replace Abstract: The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experimentsite{hannay
arXiv:2605.17151v1 Announce Type: new Abstract: In sales and marketing, customer segmentation is an important tool for formulating strategies for customer treatment and supply chain management. Most s
arXiv:2605.17071v1 Announce Type: new Abstract: Radiology report generation (RRG) aims to automatically produce clinically accurate textual reports from medical images. Existing methods predominantly
arXiv:2605.18229v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are a core interpretability tool for large language models, and progress on SAE architectures depends on benchmarks that re
arXiv:2605.17461v1 Announce Type: cross Abstract: Whether an interviewee's honest and deceptive responses can be detected by facial expression signals in videos has been debated and requires further r
arXiv:2605.16579v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion is a powerful paradigm for streaming and interactive video generation. However, its reliance on softmax self-attenti
arXiv:2605.18535v1 Announce Type: new Abstract: The bottleneck of useful agentic intelligence has shifted from compressing world knowledge into a single model to executing a coordinated system. This p
arXiv:2605.18379v1 Announce Type: new Abstract: Correlated-noise mechanisms are among the most promising approaches for improving the utility of differentially private model training, but rigorous gua
arXiv:2605.18194v1 Announce Type: new Abstract: While Multi-Modal Large Language Models (MLLMs) demonstrate impressive capabilities in general reasoning, their embodied spatial intelligence remains ha
arXiv:2605.16324v1 Announce Type: new Abstract: Financial market forecasting is inherently uncertain, yet most deep learning approaches rely on point predictions that provide only single-value estimat
arXiv:2605.16728v1 Announce Type: new Abstract: This paper proposes a minimal architecture for body-grounded perspective formation in artificial agents. Extending prior work, the model introduces an i
arXiv:2605.16438v1 Announce Type: cross Abstract: Federated Learning (FL) trains a global model across decentralized clients while preserving data privacy, but at scale it is vulnerable to malicious u
arXiv:2605.17110v1 Announce Type: new Abstract: Query clustering organizes queries into groups that reflect shared latent capability demands, enabling capability-aware LLM evaluation. Existing cluster