Knowledge catalogue
arXiv:2604.09700v1 Announce Type: cross Abstract: Constructing high-resolution 3D geological models from sparse 1D borehole and 2D surface data is a highly ill-posed inverse problem. Traditional heuri
arXiv:2603.08942v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have demonstrated remarkable zero-shot capabilities, yet adapting these models to specialized
arXiv:2509.17458v3 Announce Type: replace-cross Abstract: Text-to-image diffusion models, such as Stable Diffusion, can produce high-quality and diverse images but often fail to achieve compositional
This r/ollama thread discusses using Ollama as a local model provider for OpenAI's Codex CLI, covering configuration and setup. Open models can be used with OpenAI's Codex CLI through Ollama, allowing
arXiv:2508.20640v2 Announce Type: replace Abstract: Preserving facial identity under extreme stylistic transformation remains a major challenge in generative art. In graffiti, a high-contrast, abstrac
arXiv:2604.11007v1 Announce Type: new Abstract: Semantic segmentation of 3D point cloud scenes is a crucial task for various applications. In real-world scenarios, training segmentation models often f
arXiv:2604.11581v1 Announce Type: new Abstract: LLM evaluations drive which models get deployed, which safety standards get adopted, and which research conclusions get published. Yet these scores carr
arXiv:2507.03336v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly tasked with invoking enterprise APIs, yet they routinely falter when near-duplicate tools vie for the
arXiv:2603.07462v2 Announce Type: replace Abstract: Determining whether AI systems process information similarly to humans is central to cognitive science and trustworthy AI. While modern AI models ca
arXiv:2602.01064v2 Announce Type: replace Abstract: Knowledge distillation has emerged as a pivotal technique for transferring knowledge from stronger large language models (LLMs) to smaller, more eff
arXiv:2604.10297v1 Announce Type: cross Abstract: Composed Image Retrieval (CIR) retrieves target images using a reference image paired with modification text. Despite rapid advances, all existing met
arXiv:2502.19056v2 Announce Type: replace-cross Abstract: Fatigue modeling is essential for motion synthesis tasks to model human motions under fatigued conditions and biomechanical engineering applic
arXiv:2604.10678v1 Announce Type: new Abstract: Social bot detection is critical to the stability and security of online social platforms. However, current state-of-the-art bot detection models are la
arXiv:2604.10332v1 Announce Type: new Abstract: We present the progress of the GPT family from GPT-3 through GPT-3.5, GPT-4, GPT-4 Turbo, GPT-4o, GPT-4.1, and the GPT-5 family. Our work is comparative
arXiv:2604.11104v1 Announce Type: new Abstract: This paper presents an empirical study of a multi-model zero-shot pipeline for knowledge graph construction and exploitation, executed entirely through
arXiv:2604.09923v1 Announce Type: new Abstract: Text-to-image (T2I) models, and their encoded biases, increasingly shape the visual media the public encounters. While researchers have produced a rich
This Reddit thread discusses a user's experience attempting LoRA fine-tuning of the Gemma 4 26B-A4B model on a 16GB VRAM GPU, where training loss decreases normally but the resulting model degenerates
arXiv:2604.11590v1 Announce Type: new Abstract: Nowadays, pretrained models are increasingly used as general-purpose backbones and adapted at test-time to downstream environments where target data are
arXiv:2502.14644v5 Announce Type: replace Abstract: Long context understanding remains challenging for large language models due to their limited context windows. This paper introduces Long Input Fine
arXiv:2603.22816v3 Announce Type: replace-cross Abstract: Language models increasingly show their work by writing step-by-step reasoning before answering. But are these steps genuinely used, or is the
arXiv:2601.14671v2 Announce Type: replace Abstract: Autoregressive (AR) visual generators model images as sequences of discrete tokens and are trained with a next-token likelihood objective. This stri
arXiv:2604.10603v1 Announce Type: cross Abstract: Large language models are transforming all areas of academia and industry, attracting the attention of researchers, professionals, and the general pub
arXiv:2604.11762v1 Announce Type: new Abstract: Deep learning underpins a wide range of applications in MRI, including reconstruction, artifact removal, and segmentation. However, progress has been dr
arXiv:2604.11102v1 Announce Type: new Abstract: Current multimodal large language models (MLLMs) have demonstrated remarkable capabilities in short-form video understanding, yet translating long-form
The Ostris AI Toolkit added immediate, day-zero support for training LoRA adapters on top of Baidu's ERNIE-Image model, continuing the toolkit's pattern of rapidly integrating newly released image gen
arXiv:2604.10451v1 Announce Type: new Abstract: Despite recent advancements in the field of medical image analysis with the use of pretrained foundation models, the issue of distribution shifts betwee
arXiv:2604.10030v1 Announce Type: new Abstract: Video diffusion models have achieved remarkable progress in generating high-quality videos. However, these models struggle to represent the temporal suc
arXiv:2512.05564v2 Announce Type: replace Abstract: Recent advances in video generation have shown remarkable potential for constructing world simulators. However, current models still struggle to pro
arXiv:2508.19600v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is crucial for deploying efficient object detection models, like YOLO, on resource-constrained devices. However, th
arXiv:2604.10188v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have significantly advanced automated Radiology Report Generation (RRG). However, existing methods implicitly assume high-
arXiv:2604.10212v1 Announce Type: new Abstract: Language models can be used to identify relationships between financial entities in text. However, while structured output mechanisms exist, prompting-b
arXiv:2604.11263v1 Announce Type: cross Abstract: Accurate and efficient surrogate models for aerodynamic surface pressure fields are essential for accelerating aircraft design and analysis, yet deter
arXiv:2604.09731v1 Announce Type: cross Abstract: Tree-based speculative decoding accelerates autoregressive generation by verifying a branching tree of draft tokens in a single target-model forward p
arXiv:2604.10286v1 Announce Type: new Abstract: Autonomous language-model agents increasingly rely on installable skills and tools to complete user tasks. Static skill auditing can expose capability s
arXiv:2604.10123v1 Announce Type: new Abstract: Dysarthric speech severity assessment typically requires trained clinicians or supervised models built from labelled pathological speech, limiting scala
arXiv:2602.18679v2 Announce Type: replace Abstract: Large-scale foundation models for scientific machine learning adapt to physical settings unseen during training, such as zero-shot transfer between
Two major shifts will be seen in Agentic AI after Harness and YOU MUST KNOW. 1. Workflow design of your agents matters a lot more than any frontier model selection. Till now we have mostly focused on
arXiv:2506.02387v3 Announce Type: replace Abstract: Recent advancements in Vision Language Models (VLMs) have expanded their capabilities to interactive agent tasks, yet existing benchmarks remain lim
arXiv:2604.10787v1 Announce Type: new Abstract: Idiomatic reasoning, deeply intertwined with metaphor and culture, remains a blind spot for contemporary language models, whose progress skews toward su
arXiv:2604.10990v1 Announce Type: cross Abstract: Scientific claim verification, the task of determining whether claims are entailed by scientific evidence, is fundamental to establishing discoveries
arXiv:2604.08755v1 Announce Type: cross Abstract: Computational models support high-stakes decisions across engineering and science, and practitioners increasingly seek probabilistic predictions to qu
arXiv:2604.09445v1 Announce Type: new Abstract: Precise and real-time visual localization is critical for applications like AR/VR and robotics, especially on resource-constrained edge devices such as
arXiv:2604.08974v1 Announce Type: new Abstract: Uncertainty quantification is a set of techniques that measure confidence in language models. They can be used, for example, to detect hallucinations or
arXiv:2604.08694v1 Announce Type: new Abstract: How do you build a sign language recognizer that works on a phone? That question drove this work. We built EfficientSign, a lightweight model which take
arXiv:2604.08931v1 Announce Type: new Abstract: Human cognitive development is shaped not only by individual effort but by structured social interaction, where role-based exchanges such as those betwe
arXiv:2511.03913v2 Announce Type: replace-cross Abstract: Deep diffusion models have revolutionized image generation by producing high-quality outputs. However, achieving specific objectives with thes
arXiv:2604.08896v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have accelerated progress in domain-oriented AI, yet their development in geoscience and rem
arXiv:2604.09075v1 Announce Type: new Abstract: Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system poli
arXiv:2604.09443v1 Announce Type: cross Abstract: Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, and more-each carrying different level
arXiv:2604.09514v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled the large-scale generation of highly fluent and deceptive news-like content. While prior wo
This Reddit post on r/ollama likely discusses the concept and usage of a 'Master AI Orchestrator' CLI tool — a command-line interface designed to coordinate and manage multiple AI agents or models, de
arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag
arXiv:2604.09181v1 Announce Type: new Abstract: Diffusion models and their variations, such as rectified flows, generate diverse and high-quality images, but they are still hindered by slow iterative
arXiv:2602.15313v2 Announce Type: replace Abstract: AI Memory, specifically how models organizes and retrieves historical messages, becomes increasingly valuable to Large Language Models (LLMs), yet e
arXiv:2604.08923v1 Announce Type: new Abstract: Dimensional Aspect-Based Sentiment Analysis (DimABSA) extends traditional ABSA from categorical polarity labels to continuous valence-arousal (VA) regre
arXiv:2604.09021v1 Announce Type: cross Abstract: Auditory large language models (ALLMs) have demonstrated strong general capabilities in audio understanding and reasoning tasks. However, their reliab
This Reddit post discusses how open-source AI models have advanced to rival GPT-4-level performance and can be run locally for free using Ollama — a tool that lets users download and manage large lang
arXiv:2602.04674v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reprodu
arXiv:2511.20068v2 Announce Type: replace Abstract: Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large l
arXiv:2602.02188v2 Announce Type: replace Abstract: While large language models (LLMs) have shown strong performance in math and logic reasoning, their ability to handle combinatorial optimization (CO