Knowledge catalogue
arXiv:2503.15845v2 Announce Type: replace Abstract: Network-wide Traffic State Estimation (TSE), which aims to infer a complete image of network traffic states with sparsely deployed sensors, plays a
arXiv:2604.16919v1 Announce Type: cross Abstract: Diffusion models (DMs) have recently shown remarkable performance on inverse problems (IPs). Optimization-based methods can fast solve IPs using DMs a
Ollama does not officially support TPUs or NPUs currently , though community discussions and projects are exploring integration possibilities. The Reddit post likely addresses user questions about whe
arXiv:2511.19202v2 Announce Type: replace Abstract: 3D Gaussian Splatting can exploit frustum culling and level-of-detail strategies to accelerate rendering of scenes containing a large number of prim
arXiv:2604.16519v1 Announce Type: new Abstract: In the field of online reinforcement learning (RL), traditional Gaussian policies and flow-based methods are often constrained by their unimodal express
arXiv:2604.16523v1 Announce Type: new Abstract: This paper proposes a novel privacy-preserving semantic segmentation method that can use independent keys for each client and image. In the proposed met
arXiv:2510.16054v2 Announce Type: replace-cross Abstract: When users submit queries to Large Language Models (LLMs), their prompts can often contain sensitive data, forcing a difficult choice: Send th
arXiv:2604.17476v1 Announce Type: cross Abstract: Multi-user virtual reality enables immersive interaction. However, rendering avatars for numerous participants on each headset incurs prohibitive comp
arXiv:2604.16858v1 Announce Type: new Abstract: Image Quality Assessment (IQA) models are increasingly deployed as perceptual critics to guide generative models and image restoration. This role demand
arXiv:2604.17321v1 Announce Type: new Abstract: Face morphing attacks pose a substantial risk to the reliability of face recognition systems used in passport issuance, border control, and digital iden
arXiv:2604.17530v1 Announce Type: cross Abstract: Posture is a critical factor for beginning instrumental learners. Most students receive instruction only once a week, and during the intervals between
Refocus IC LoRA is a specialized AI model addon for LTX 2.3 that uses machine learning to restore clarity to out-of-focus video footage. Created by @MedOumoumad, it integrates with the ComfyUI workflo
arXiv:2604.18145v1 Announce Type: new Abstract: Automated medical report generation for 3D PET/CT imaging is fundamentally challenged by the high-dimensional nature of volumetric data and a critical s
arXiv:2511.05993v3 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for enhancing the reasoning capabilities of large language
arXiv:2604.16683v1 Announce Type: cross Abstract: Imitation learning has enabled robots to acquire complex visuomotor manipulation skills from demonstrations, but deployment failures remain a major ob
arXiv:2604.17504v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training substantially improves remote sensing vision-language models (RS-VLMs). However, when handling complex remote
arXiv:2604.16815v1 Announce Type: cross Abstract: Quantum error mitigation (QEM) provides a practical route for estimating reliable observables on noisy intermediate-scale quantum (NISQ) devices. Trad
arXiv:2411.15115v3 Announce Type: replace-cross Abstract: Recent text-to-video (T2V) diffusion models have made remarkable progress in generating high-quality videos. However, they often struggle to a
arXiv:2604.18464v1 Announce Type: new Abstract: Semantic Tube Prediction (STP) leverages representation geometric to regularize LLM hidden-state trajectories toward locally linear geodesics during fin
arXiv:2604.18034v1 Announce Type: new Abstract: We present SignDPO, a novel multi-level Direct Preference Optimisation (DPO) framework designed to enhance the alignment of skeleton-based Sign Language
arXiv:2601.21159v2 Announce Type: replace Abstract: High-resolution remote sensing images contain densely distributed objects with pronounced scale variations and complex boundaries, which impose high
arXiv:2603.27437v2 Announce Type: replace Abstract: Large vision-language models (VLMs) still struggle with reliable 3D spatial reasoning, a core capability for embodied and physical AI systems. This
arXiv:2604.17880v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved great success on general robotic tasks, but still face challenges in fine-grained spatiotemporal man
arXiv:2604.17773v1 Announce Type: new Abstract: Three-dimensional (3D) medical image enhancement, including denoising and super-resolution, is critical for clinical diagnosis in CT, PET, and MRI. Alth
arXiv:2604.18573v1 Announce Type: new Abstract: Despite recent progress, vision-language encoders struggle with two core limitations: (1) weak alignment between language and dense vision features, whi
arXiv:2604.17139v1 Announce Type: new Abstract: Multi-agent large language model (LLM) architectures increasingly rely on response-level aggregation, such as Majority Voting (MAJ), to raise reasoning
arXiv:2604.16502v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning, while recent extensions that incorpo
arXiv:2603.08096v3 Announce Type: replace Abstract: Localizing objects and parts from natural language in 3D space is essential for robotics, AR, and embodied AI, yet existing methods face a trade-off
arXiv:2604.18001v1 Announce Type: new Abstract: Super-resolution (SR) models are attracting growing interest for enhancing minimally invasive surgery and diagnostic videos under hardware constraints.
arXiv:2604.16542v1 Announce Type: cross Abstract: Safety guardrails have become an active area of research in AI safety, aimed at ensuring the appropriate behavior of large language models (LLMs). How
v0.21.1-rc1 is a release candidate for Ollama, an open-source tool for running machine learning models locally. The release candidate phase indicates testing and bug-fixing before the stable v0.21.1 r
arXiv:2604.17656v1 Announce Type: cross Abstract: Video-to-music (V2M) is the fundamental task of creating background music for an input video. Recent V2M models achieve audiovisual alignment by typic
arXiv:2601.15724v2 Announce Type: replace Abstract: Long-form video understanding remains a fundamental challenge for current Video Large Language Models. Most existing models rely on static reasoning
arXiv:2508.15229v3 Announce Type: replace Abstract: Small Language Models (SLMs) provide computational advantages in resource-constrained environments, yet memory limitations remain a critical bottlen
Users training LTX-2.3 LoRAs on RTX 4090s typically use the official ltx-trainer tool, though the model officially targets H100 GPUs with lower VRAM setups requiring gradient checkpointing and reduced
This Reddit discussion explores sampler and scheduler preferences within the Stable Diffusion community, where samplers guide the process of turning noise into an image and schedulers control how nois
arXiv:2604.17422v1 Announce Type: new Abstract: Long video understanding remains a formidable challenge for Multimodal Large Language Models (MLLMs) due to the prohibitive computational cost of proces
arXiv:2602.17909v2 Announce Type: replace Abstract: Diffusion-based approaches have recently demonstrated strong performance for single-image novel view synthesis by conditioning generative models on
arXiv:2604.16234v1 Announce Type: cross Abstract: Academic integrity continues to face the persistent challenge of examination cheating. Traditional invigilation relies on human observation, which is
arXiv:2604.15609v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) for black-box models accessible only via APIs remains a largely unexplored challenge. Existing approaches such as post-hoc
arXiv:2604.15622v1 Announce Type: new Abstract: Language-aligned vision foundation models (VFMs) enable versatile visual understanding for always-on contextual AI, but their deployment on edge devices
B8852 is a release of llama.cpp, an LLM inference library in C/C++ . This build tag likely contains bug fixes, performance improvements, and feature updates from the llama.cpp development cycle, which
b8853 is a release of llama.cpp , the open-source C/C++ library for running large language model inference. The project enables LLM inference with minimal setup and state-of-the-art performance on a w
Release b8855 addresses a crash in llama-tokenize when using the vocab_only flag with GLM-DSA models and fixes a crash in print_info for GLM-DSA when vocab_only is set. This is a bugfix release for th
B8857 is an intermediate build release from the llama.cpp project, which is a C/C++ implementation that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of har
Release b8859 is a version of llama.cpp, an open-source project that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. The llama.cpp project uses a
Release b8860 of llama.cpp addresses a tensor-parallel computation issue by fixing delayed AllReduce on Gemma-4 MoE models, including optimizations to skip forward past unused nodes and allow chains o
Release b8861 of llama.cpp removed /api endpoints from the server, including the /api/tags endpoint. The release was published on April 20, 2026. This is a maintenance update to the llama.cpp project,
Release b8862 of llama.cpp includes a fix for 'mtmd: correct get_n_pos / get_decoder_pos' and provides compiled binaries for multiple platforms including macOS, Linux, Windows, Android, and openEuler
arXiv:2604.15414v1 Announce Type: cross Abstract: Continual reinforcement learning must balance retention with adaptation, yet many methods still rely on single-model preservation, committing to one e
Color shift flicker in Stable Diffusion refers to a known bug where images shift toward magenta and darker shadows during img2img processing . ControlNet can help address color shift by improving colo
arXiv:2604.15814v1 Announce Type: new Abstract: Hand-eye calibration through visual localization is a critical capability for robotic manipulation in open-world environments. However, most deep learni
arXiv:2604.15768v1 Announce Type: cross Abstract: AI-driven methods have demonstrated considerable success in tackling the central challenge of accurately solving the Schrodinger equation for complex
arXiv:2604.15594v1 Announce Type: cross Abstract: Modern datacenters schedule heterogeneous workloads across geo-distributed sites with diverse compute capacities, electricity prices, and thermal cond
arXiv:2510.20299v3 Announce Type: replace-cross Abstract: Brain tumors are a challenging problem in neuro-oncology, where early and precise diagnosis is important for successful treatment. Deep learni
arXiv:2403.18026v2 Announce Type: replace-cross Abstract: High-throughput biological imaging is often constrained by a trade-off between acquisition speed and image quality. Fast imaging modalities, s
arXiv:2604.15750v1 Announce Type: cross Abstract: Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive language generation due to their potential for parallel dec
DFlash for Qwen3.6-35B-A3B just dropped ⚡ The community was running the day-1 preview before we even finished training. Now it's done: ✅ Training complete ✅ Validation passed ✅ Weights finalized ↓ Go
arXiv:2604.16083v1 Announce Type: new Abstract: With the rapid advancement of deep generative models, realistic fake images have become increasingly accessible, yet existing localization methods rely
arXiv:2604.16104v1 Announce Type: cross Abstract: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Conventional computed tomography (CT) imaging, while essential fo