Knowledge catalogue
arXiv:2412.02798v3 Announce Type: replace Abstract: We consider the problem of reconstructing a HxWx31 hyperspectral image from a Himes W grayscale snapshot measurement that is captured using only a s
arXiv:2606.32023v1 Announce Type: cross Abstract: Forest attributes are essential for national-scale resource monitoring. Airborne LiDAR metrics are among the auxiliary variables most strongly correla
arXiv:2606.31177v1 Announce Type: new Abstract: Autonomous driving systems benefit from high-definition (HD) maps that provide critical information about road infrastructure. The online construction o
arXiv:2606.30813v1 Announce Type: cross Abstract: Deep neural networks with repeated architectural blocks, such as transformers, often exhibit structured relationships across layers that emerge during
arXiv:2606.31683v1 Announce Type: cross Abstract: Diffusion models have emerged as a dominant paradigm in generative modeling, enabling high-fidelity sampling from complex data distributions. Despite
arXiv:2606.31808v1 Announce Type: new Abstract: Language model systems built around proprietary APIs often operate on a token-based cost model. This becomes prohibitively expensive in the context of l
arXiv:2606.30963v1 Announce Type: cross Abstract: Repository-grounded automated repair is often reported as a single end-to-end capability, which hides distinct failure modes such as poor file targeti
Local AI Summit is tomorrow at AIE World Fair Kicking off w/ a Local AI & OSS State of the Union panel at 10:45am We'll demo GLM 5.2 running in the room on a DGX Station. Epic panels. See you there 🤙
arXiv:2606.31699v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) have recently been proposed as interpretable tools for concept-level manipulation, under the assumption that isolated featu
arXiv:2606.31981v1 Announce Type: cross Abstract: Creating photorealistic, animatable 3D human avatars from monocular images still largely depends on Linear Blend Skinning (LBS) and parametric body mo
arXiv:2606.30656v1 Announce Type: cross Abstract: Artificial Intelligence (AI) has the potential to be transformative for development, but Africa is currently facing a fragmented and challenging 'AI d
arXiv:2506.09919v4 Announce Type: replace Abstract: We introduce MetricHMSR, a novel framework for recovering metric human meshes and 3D scenes from a single monocular image. Existing methods struggle
Nano Banana 2 Lite is an image editing tool or model available through ComfyUI, a node-based interface for AI image generation and manipulation. This resource likely provides a lightweight version of
Nano Banana 2 Lite is now in Comfy. The fastest, cheapest model in the Nano Banana family. → 4-second image gen → $0.034 per 1K images If your pipeline runs on iteration volume, this changes the game.
Nano Banana 2 Lite is a text-to-image model optimized for efficiency and speed, likely designed for use within the ComfyUI node-based interface. This lightweight version of the model enables users to
arXiv:2606.30836v1 Announce Type: new Abstract: Explainability in Many-Objective Optimization (MaO) is currently hindered by the escalating complexity of the Pareto front, which renders the relationsh
arXiv:2606.31148v1 Announce Type: cross Abstract: 3D Visual Grounding (3DVG) aims to localize target objects in 3D scenes given natural language descriptions. Existing approaches typically perform rea
arXiv:2409.10141v3 Announce Type: replace Abstract: Detailed and photorealistic 3D human modeling is essential for various applications and has seen tremendous progress. However, full-body reconstruct
arXiv:2506.22075v2 Announce Type: replace Abstract: Reasoning is a hallmark of human intelligence, enabling adaptive decision-making in complex unfamiliar scenarios. In contrast, machine intelligence
arXiv:2507.11061v3 Announce Type: replace-cross Abstract: Recent advances in 3D neural representations and instance-level editing models have enabled the efficient creation of high-quality 3D content.
arXiv:2606.31248v1 Announce Type: cross Abstract: Kilometer-scale convection shapes precipitation extremes, tropical organization, and cloud feedbacks, but most global atmospheric models approximate t
arXiv:2606.32002v1 Announce Type: new Abstract: Language models are increasingly taught from synthetic question--answer (QA) supervision: a model generates questions about a document, answers them fro
arXiv:2606.31166v1 Announce Type: new Abstract: Text-attributed graphs (TAGs), where each node carries a natural language description, require models to jointly reason over text and graph topology. Ex
arXiv:2606.31036v1 Announce Type: new Abstract: Specialist epilepsy expertise is scarce in resource-constrained settings, making LLM-based decision support attractive for frontline clinicians managing
arXiv:2606.31029v1 Announce Type: new Abstract: Generative models have achieved remarkable progress, yet applying them to satellite imagery remains challenging. Unlike natural imagery, satellite scene
arXiv:2606.31207v1 Announce Type: new Abstract: The rapid advance of smart cities increasingly depends on trajectory data mining, yet underrepresented demographic groups, particularly the elderly, are
arXiv:2606.30815v1 Announce Type: cross Abstract: Recent work suggests that transformer language models show a bias towards human languages over unnatural ('impossible') languages argued to be unacqui
arXiv:2606.31575v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a powerful tool for propelling Large Language Models (LLMs) beyond imitation-based training towards more robust r
arXiv:2606.30586v1 Announce Type: cross Abstract: Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequent
arXiv:2606.28751v1 Announce Type: new Abstract: We propose a path-space formulation of prediction in AI world models. Rather than sequences of one-step conditional distributions, we argue that a world
A study from @Stanford showed that 71.3% of chatgpt queries could be accurately answered by a local model. I suspect a major part of enterprise AI workloads could be run locally too for free (compared
Ahmad Osman discusses the technological and practical reasons why locally-run AI models are becoming increasingly competitive with cloud-based alternatives, likely covering improvements in model effic
arXiv:2606.29194v1 Announce Type: new Abstract: Automated alpha mining holds the scoring function fixed and varies the search algorithm over it. A search that converges against a fixed scorer overfits
arXiv:2606.29118v1 Announce Type: cross Abstract: Graph-based narrative extraction relies on a coherence function to score transitions between events, but the coherence metrics in current use are defi
arXiv:2606.29181v1 Announce Type: cross Abstract: Detecting and localizing defects in 3D point clouds is challenging because abnormal samples are scarce and diverse, while training is often limited to
arXiv:2606.28683v1 Announce Type: new Abstract: Large Language Models (LLMs) often face ethical tradeoffs in which several responses may be defensible but express different priorities, such as fairnes
b9843 is a release of llama.cpp that reverts 'sched: reintroduce less synchronizations during split compute (#20793)' . The release includes pre-built binaries for multiple platforms including macOS,
llama.cpp is a C/C++ implementation for LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. Release b9844 is an intermediate build of the llama.cpp project f
Release build b9846 is an intermediate build of llama.cpp, an open-source C/C++ project for LLM inference. The llama.cpp project is the main playground for developing new features for the ggml library
B9847 is a build release in the llama.cpp project, which is an open-source tool that enables LLM inference with minimal setup on a wide range of hardware . This specific build release likely contains
llama.cpp uses continuous build-tagged releases rather than traditional semantic versions. Release b9848 is a specific build from the ggml-org/llama.cpp project, which is an LLM inference implementati
b9849 is a build release from llama.cpp, which enables LLM inference in C/C++ . The release represents an intermediate build version of the llama.cpp library, a widely-used open-source project for run
Release b9850 is a version of llama.cpp, an open-source software library for large language model inference developed alongside the GGML tensor library. This release likely includes updates, bug fixes
B9851 is a release of llama.cpp, an LLM inference project written in C/C++ . The release represents a version update in the llama.cpp development timeline maintained on GitHub. This build tag typicall
arXiv:2606.30576v1 Announce Type: cross Abstract: Cross-view object geo-localization (CVOGL) aims to locate a target object from a query view (e.g., ground or drone) within a geo-tagged reference imag
arXiv:2606.29416v1 Announce Type: cross Abstract: Can a vision model truly see an object, or does it only fit surface-level visual cues? Following Wittgenstein's view that the limits of language are t
arXiv:2606.28724v1 Announce Type: cross Abstract: Understanding and localizing subtle changes between paired images is critical for tasks such as surveillance and image editing. However, traditional I
arXiv:2606.30226v1 Announce Type: new Abstract: Hessian spectral properties are a standard tool in analysing neural-network training, with eigenvalues linked to sharpness, generalization, and optimiza
arXiv:2512.02453v2 Announce Type: replace Abstract: Existing stylized motion generation models have shown their remarkable ability to understand specific style information from the style motion, and i
arXiv:2603.05905v2 Announce Type: replace Abstract: Small object detection in unmanned aerial vehicle (UAV) imagery is challenging because high-altitude viewpoints produce severe scale variation, weak
arXiv:2606.29825v1 Announce Type: new Abstract: Modeling tethered space systems is critical for advanced orbital operations. Flexible components such as tethers and space nets are integral to these sy
arXiv:2606.28560v1 Announce Type: new Abstract: We study sparse self-attention in which each query attends to a dense local window plus a set of Fibonacci-spaced offsets, with a per-layer scalar alpha
arXiv:2606.29377v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models by grounding responses in external evidence, yet real-world deploy
arXiv:2606.30499v1 Announce Type: new Abstract: Federated Learning often suffers under non-independently and identically distributed data, where a single global model may fail to represent the diversi
arXiv:2606.28725v1 Announce Type: new Abstract: Automated toxicity moderation systems operate in dynamic online environments where harmful behavior evolves through coded language, shifting targets, an
arXiv:2606.29023v1 Announce Type: cross Abstract: Spatio-temporal grounding in long videos requires precise temporal localization and robust object tracking conditioned on natural-language queries. Wh
arXiv:2606.28920v1 Announce Type: new Abstract: Remote sensing visual grounding (RSVG) aims to locate specific objects in high-resolution RS imagery using free-form natural language descriptions. Whil
arXiv:2606.28391v1 Announce Type: cross Abstract: The wide use of Convolutional Neural Networks (CNN) in numerous domains and real-world classification applications is justified by their high precisio
arXiv:2606.29773v1 Announce Type: new Abstract: Graphs are widely used to model relational systems, with applications in domains such as social networks, finance, and biomedicine. Graph neural network
arXiv:2606.28513v1 Announce Type: cross Abstract: Positron emission tomography (PET) seeks to balance diagnostic quality with ra-diation dose. Low-count PET noise is non-Gaussian, non-stationary, and