Knowledge catalogue
arXiv:2604.24997v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation requires assigning pixel-level semantic labels while supporting an open and unrestricted set of categories. Traini
arXiv:2604.25039v1 Announce Type: new Abstract: Large Language Models (LLMs) solve many reasoning tasks via chain-of-thought (CoT) prompting, but smaller models (about 7 to 8B parameters) still strugg
arXiv:2604.24972v1 Announce Type: new Abstract: Clinical abnormality grounding for rare diseases is often hindered by data scarcity, making supervised fine-tuning impractical and single-pass inference
arXiv:2604.25482v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for narrative generation, but their use in complex, multi-layered role-playing game (RPG) world
Quanty AI is a local AI companion playground built with Ollama as the backend, featuring animated pixel art graphics and interactive micro fiction experiences. The project integrates agent skills to e
Wan2GP users can explore high-quality output modes like LTX 2 DEV HQ Mode, which is designed to produce better output at higher resolutions by using the HQ sampler with specific settings like 15 steps
📽️ Let's Explore Comfy Hub 🎤 Host: Purz ⏲️ April 29th – 3pm PST / 6pm EST 📍 Live on YouTube, X, and Twitch Today we're diving into Comfy Hub + Comfy Cloud — your gateway to exploring what's possible w
Comfy Hub appears to be an exploratory broadcast or presentation from the ComfyUI project shared via X (formerly Twitter). Based on the context, it likely discusses features, updates, or capabilities
arXiv:2604.25405v1 Announce Type: new Abstract: Camera-based 3D object detection and tracking are central to autonomous driving, yet precise 3D object localization remains fundamentally constrained by
arXiv:2604.25860v1 Announce Type: new Abstract: Machine-generated text (MGT) detection requires identifying structurally invariant signals across generation models, rather than relying on model-specif
MiMo-V2.5 is Xiaomi's multimodal AI model with native visual and audio understanding that supports up to 1 million tokens of context. The GGUF format refers to quantized versions of the model optimize
arXiv:2603.15954v2 Announce Type: replace Abstract: Real-time AI experiences call for on-device large language models (OD-LLMs) optimized for efficient deployment on resource-constrained hardware. The
The Ministral-3:3b model requires Ollama 0.13.1, which is in pre-release , and users encountering errors when running it face various issues including memory allocation problems and GPU/CPU offloading
arXiv:2511.20211v2 Announce Type: replace Abstract: Transparency-aware generation requires modeling not only RGB appearance but also alpha-based opacity and cross-layer composition, which are essentia
arXiv:2604.25276v1 Announce Type: new Abstract: Video Temporal Grounding (VTG), the task of localizing video segments from text queries, struggles in open-world settings due to limited dataset scale a
arXiv:2604.25551v1 Announce Type: new Abstract: Recurrent Graph Neural Networks (RGNNs) extend standard GNNs by iterating message-passing until some stopping condition is met. Various RGNN models have
arXiv:2604.24832v1 Announce Type: new Abstract: Masked diffusion language models (MDMs) have recently emerged as a promising alternative to standard autoregressive large language models (AR-LLMs), yet
arXiv:2601.21293v2 Announce Type: replace Abstract: Reliability-centered prognostics for rotating machinery requires early-warning signals that remain accurate under nonstationary operating conditions
Qwen3.6 27B is a 27-billion parameter language model that can achieve approximately 60 tokens per second throughput when running on dual RTX 5060 Ti GPUs with 16GB memory each, using the vLLM inferenc
arXiv:2604.05594v2 Announce Type: replace Abstract: Pixel-level annotation is costly in low-resource dermoscopy. We present RABC-Net, a reliability-aware annotation-free segmentation system that combi
arXiv:2602.20730v2 Announce Type: replace Abstract: We study efficiency as a first-class objective in Neural Combinatorial Optimization (NCO) and present ECO, an efficient learning framework that comb
arXiv:2604.25646v1 Announce Type: new Abstract: Robotic ultrasound has advanced local image-driven control, contact regulation, and view optimization, yet current systems lack the anatomical understan
arXiv:2604.25071v1 Announce Type: cross Abstract: The prevalence of biometric authentication has been on the rise due to its ease of use and elimination of weak passwords. To date, most biometric auth
SenseNova U1 is a new series of native multimodal models that unifies multimodal understanding, reasoning, and generation within a monolithic architecture, marking a fundamental paradigm shift in mult
I need to check the actual content of this post to provide an accurate summary. FLUX.2 [klein] 9B is a 9 billion parameter image generation model capable of generating images from text descriptions an
UniGenDet is a unified generative-discriminative framework that co-evolves image generation and generated image detection, aligning generation with detector-aware signals for improved authenticity and
We're open-sourcing Hy-MT1.5-1.8B-1.25bit — a 440MB translation model that runs fully offline on your phone, supports 33 languages, and outperforms Google Translate. At 1.8B parameters, it matches com
arXiv:2604.23935v1 Announce Type: new Abstract: Audio-based video object segmentation aims to locate and segment objects in videos conditioned on audio cues, requiring precise understanding of both ap
300,000 AI builders have already added their hardware to HF to instantly see what model they can run locally. To do so, go to https://huggingface.co/settings/local-apps and add your hardware specs. Yo
arXiv:2604.22858v1 Announce Type: new Abstract: Liver cancer, especially hepatocellular carcinoma (HCC), imposes a substantial global disease burden. Accurate diagnosis and prognostic assessment direc
arXiv:2604.23127v1 Announce Type: cross Abstract: Soil salinity is a major environmental challenge in coastal Bangladesh, threatening agricultural productivity and local livelihoods. This study develo
arXiv:2512.21372v2 Announce Type: replace-cross Abstract: The accurate classification of gastrointestinal diseases from endoscopic and histopathological imagery remains a significant challenge in medi
arXiv:2601.12483v2 Announce Type: replace-cross Abstract: Quantum error correction is a key ingredient for large scale quantum computation, protecting logical information from physical noise by encodi
arXiv:2604.24039v1 Announce Type: cross Abstract: Embodied AI agents increasingly rely on large language models (LLMs) for planning, yet per-step LLM calls impose severe latency and cost. In this pape
arXiv:2510.18774v4 Announce Type: replace Abstract: AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a
Release b8953 of llama.cpp adds Q1_0 quantization support for WebGPU, including fast matmul and matvec kernels and optimized shared memory initialization. The release was published on April 28 and inc
llama.cpp is a C/C++ implementation for LLM inference. Build b8954 is a release version from the ggml-org/llama.cpp repository that likely includes bug fixes, optimizations, or new features added sinc
b8957 is a release of llama.cpp that includes spec parameter refactoring changes , featuring modifications to parameter handling and model specifications. The llama.cpp project enables LLM inference w
b8958 is a release of llama.cpp, a C/C++ library for LLM inference . The project uses rapid release cycles with frequent version tags tracking incremental updates and improvements to the codebase. Thi
B8960 is a build release of llama.cpp, an open-source C/C++ project for running large language models locally with minimal setup and optimized performance across various hardware platforms. It is one
B8963 is a build release of llama.cpp, the C/C++ implementation of LLM inference. Llama.cpp is an open-source project that enables efficient language model execution on consumer hardware with minimal
b8964 is a release of llama.cpp, a C/C++ library for LLM inference . The release likely includes bug fixes, performance optimizations, or new features as part of the project's continuous development c
b8966 is one of the latest releases in the llama.cpp project , a C/C++ implementation for efficient LLM inference. This release represents an intermediate development build in the llama.cpp repository
llama.cpp b8967 is an intermediate build release of llama.cpp, a C/C++ implementation for LLM inference with minimal setup and state-of-the-art performance. The project follows a rapid release cycle w
arXiv:2604.24665v1 Announce Type: cross Abstract: This paper investigates whether source trustworthiness shapes Turkish evidential morphology and whether large language models (LLMs) track this sensit
arXiv:2604.23399v1 Announce Type: new Abstract: High-performance semantic segmentation has achieved significant progress in recent years, often driven by increasingly large backbones and higher comput
arXiv:2604.24622v1 Announce Type: cross Abstract: Flow-based vision-language-action (VLA) policies offer strong expressivity for action generation, but suffer from a fundamental inefficiency: multi-st
arXiv:2604.23137v1 Announce Type: cross Abstract: Early detection and classifying brain tumors using Magnetic Resonance Imaging (MRI) images is highly important but difficult to extract in medical ima
arXiv:2604.23088v1 Announce Type: cross Abstract: We present Code Broker, a multi agent system built with Google Agent Development Kit ADK that analyses Python code from files, local directories, or G
arXiv:2604.23016v1 Announce Type: cross Abstract: AI-powered generative models have significantly expanded the possibilities for editing, manipulating, and creating high-quality images. Particularly,
arXiv:2604.24492v1 Announce Type: cross Abstract: Designing deep networks that meet strict latency and accuracy constraints on edge accelerators increasingly relies on hardware-aware optimization, inc
arXiv:2604.23829v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) extract millions of interpretable features from a language model, but flat feature inventories aren't very useful on their ow
arXiv:2604.24426v1 Announce Type: new Abstract: AI-generated media are advancing rapidly, raising pressing concerns for content authenticity and digital trust. We introduce DYMAPIA, a multi-domain Dee
arXiv:2604.24146v1 Announce Type: new Abstract: Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imagin
arXiv:2604.24078v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) have become increasingly popular in recent years due to their superior predictive performance by combining both s
arXiv:2604.24104v1 Announce Type: new Abstract: Fine-tuned autoregressive models for graph-to-sequence generation (G2S) often struggle with factual grounding and edit sensitivity. To tackle these issu
arXiv:2604.23350v1 Announce Type: cross Abstract: Deep generative models and neural operators have demonstrated significant potential for 3D aerodynamic inference. However, they often face inherent ch
LingBot-World-Fast successfully preserves the structural integrity and physical logic of the teacher model , achieving acceleration that introduces a necessary trade-off in theoretical upper-bound qua
arXiv:2604.23134v1 Announce Type: new Abstract: Accurate molecular representations are critical for drug discovery, and a central challenge lies in capturing the chemical environment of molecular frag
arXiv:2604.23318v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) performs coarse-grained credit assignment in reinforcement learning with verifiable rewards (RLVR) by assignin