Knowledge catalogue
arXiv:2606.31695v1 Announce Type: new Abstract: The performance of deep spiking neural networks (SNNs) often relies on batch normalization (BN). However, the advanced dynamic BN variants used in state
arXiv:2606.30551v1 Announce Type: cross Abstract: Calculation of binding energies for protein-ligand molecular systems requires accurate treatment of the electronic structure, a quantum chemistry prob
arXiv:2506.07069v2 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, combining high-quality reconstruction with efficien
The financial services industry (FSI) operates under a unique set of non-negotiable requirements: the need for strict regulatory compliance, sub-millisecond transactional speeds, and security that ver
arXiv:2503.19501v2 Announce Type: replace-cross Abstract: Falls among elderly residents in assisted living homes pose significant health risks, often leading to injuries and a decreased quality of lif
arXiv:2606.29966v1 Announce Type: cross Abstract: Quantum computing provides a powerful paradigm for representing and transforming high-dimensional information through superposition, entanglement, and
arXiv:2511.10480v3 Announce Type: replace-cross Abstract: Optimizing the performance of large language models (LLMs) on large-scale AI training and inference systems requires a scalable and expressive
arXiv:2508.19094v3 Announce Type: replace Abstract: Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in st
arXiv:2606.28252v1 Announce Type: cross Abstract: Early detection of oral cancer markedly improves clinical outcomes, yet specialized diagnostic tools remain scarce in low-resource settings. Smartphon
In the agentic era, the role of the database has fundamentally changed. It is no longer a passive repository; it’s a critical context engine designed to ground generative AI apps, models and power aut
Automated lint: 49 errors, 14 warnings, 3 info
Based on available search results, I cannot find specific details about the b9814 release. However, b9814 is a build version identifier from the ggml-org/llama.cpp repository, which is a C/C++ impleme
arXiv:2606.26315v1 Announce Type: new Abstract: Disturbance-robust UAV position control is easy to demonstrate in benign simulations but much harder to make fast in approach, well behaved near the tar
arXiv:2606.25589v1 Announce Type: new Abstract: As graph neural networks (GNNs) become standard tools for critical tasks in circuit design and analysis, their security and privacy risks require carefu
arXiv:2405.01741v4 Announce Type: replace-cross Abstract: Reliability of AI systems is a fundamental concern for the successful deployment and widespread adoption of AI technologies. Unfortunately, th
arXiv:2606.24780v1 Announce Type: new Abstract: Progress in deep learning is, at scale, more a matter of systems engineering than of modelling: the behaviour of a model in training (its throughput, it
arXiv:2606.24049v1 Announce Type: new Abstract: In robot learning, scaling training datasets across diverse embodiments and environments has become a dominant paradigm for learning generalizable robot
Written by: Chester Sng, Pete Boonyakarn, Logeswaran Nadarajan Introduction In early 2026, Mandiant identified a threat actor targeting SD-WAN infrastructure at a service provider. After gaining initi
arXiv:2606.20031v2 Announce Type: replace Abstract: Dynamic environmental changes, confined workspaces, and stringent real-time constraints make pathfinding in Robotic Mobile Fulfillment Systems (RMFS
arXiv:2606.22278v1 Announce Type: cross Abstract: Ensuring safety of learning-enabled robotic manipulation across diverse embodiments and tasks still requires significant manual engineering. Existing
arXiv:2606.20715v1 Announce Type: new Abstract: Micro-expression recognition (MER) in realistic scenarios demands high temporal sensitivity and ecological validity, yet existing benchmarks are largely
arXiv:2606.21023v1 Announce Type: new Abstract: As Large Language Models (LLMs) deploy into mission-critical domains (e.g., finance, medicine, and law), output reproducibility has become a strict syst
arXiv:2606.13102v2 Announce Type: replace Abstract: Despite the success of vision-based generalist robotic policies, existing tactile-based policies remain tied to fixed embodiments and sensor setups.
arXiv:2505.11494v3 Announce Type: replace Abstract: Robot learning has produced remarkably effective ``black-box'' controllers for complex tasks such as dynamic locomotion on humanoids. Yet ensuring d
arXiv:2606.21866v1 Announce Type: new Abstract: Co-design of legged robots with elastic elements is challenging due to the non-differentiability of contact dynamics and mechanism engagement. This pape
arXiv:2606.22332v1 Announce Type: new Abstract: Tactile sensing is critical for contact-rich dexterous manipulation, yet it remains unclear which tactile abstractions a policy needs and when richer ta
arXiv:2606.23546v1 Announce Type: new Abstract: Transformer-based models underpin modern natural language processing but incur rapidly growing computational and energy costs. As training scales in bot
arXiv:2511.22699v4 Announce Type: replace Abstract: The landscape of high-performance image generation models is currently dominated by proprietary systems, such as Nano Banana Pro and Seedream 4.0. L
arXiv:2606.22145v1 Announce Type: new Abstract: Reinforcement learning (RL) is a powerful and convenient tool to modernize controller design. In this work, we study the zero-shot transfer of RL-based
Automated lint: 48 errors, 13 warnings, 3 info
arXiv:2606.12059v1 Announce Type: new Abstract: We address transformer attention on energy-constrained physical substrates. Softmax attention requires exponentiation and global reduction, operations w
arXiv:2503.22926v3 Announce Type: replace Abstract: Addressing the inherent low acquisition frequency limitation of 3D LiDAR to achieve high-frequency output has become a critical research focus in th
arXiv:2505.01458v2 Announce Type: replace-cross Abstract: Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, ti
arXiv:2606.09869v1 Announce Type: cross Abstract: Federated Learning (FL) combined with Split Learning (SL) is a privacy preserving paradigm that enables training deep neural networks (DNNs) on resour
arXiv:2606.10874v1 Announce Type: new Abstract: In quantum image processing, a fundamental step is encoding classical image data into quantum states. This can be achieved using methods such as Flexibl
arXiv:2606.09946v1 Announce Type: cross Abstract: Edge-AI systems increasingly require real-time CNN inference under strict energy, performance, security, and privacy constraints. Approximate computin
arXiv:2606.08584v1 Announce Type: new Abstract: Sparse coding provides a principled framework for signal representation by expressing an input as a linear combination of only a small number of basis f
arXiv:2602.21788v2 Announce Type: replace-cross Abstract: Scaling long-context capabilities is crucial for Large Language Models (LLMs). However, real-world data contain a large number of sequences wi
arXiv:2406.07318v3 Announce Type: replace Abstract: The utilisation of event cameras represents an important and swiftly evolving trend aimed at addressing the constraints of traditional video systems
arXiv:2505.20137v5 Announce Type: replace-cross Abstract: Predictive Coding (PC) offers a brain-inspired alternative to backpropagation for neural network training, described as a physical system mini
arXiv:2606.09117v1 Announce Type: cross Abstract: While Ising machines serve as advanced physical solvers for the Ising model,enabling applications in combinatorial optimization and neural network tra
arXiv:2606.09227v1 Announce Type: cross Abstract: The convergence of the 2026 European Union Safe and Sustainable by Design (SSbD) framework, Corporate Sustainability Due Diligence Directive (CSDDD),
The search results did not provide specific information about the b9564 release. Based on the context of llama.cpp releases and the pattern observed with nearby releases (b9542, b9543, b9544, etc.), I
arXiv:2509.11740v2 Announce Type: replace Abstract: Autonomous stocking in retail environments, particularly supermarkets, presents challenges due to dynamic human interactions, constrained spaces, an
Given how badly burned anyone who took Apple's 2024 WWDC Apple Intelligence announcements at face value was, I'm holding to a strict 'I'll believe it when I see it' policy for everything they announce
The search did not return specific details about the b9547 release. Based on the repository context and release naming convention, b9547 is a build number for llama.cpp, an open-source C/C++ implement
Release b9549 of llama.cpp adds support for the Gemma4 MTP model architecture . The release includes pre-built binaries for multiple platforms including macOS, Linux, Android, and Windows with various
llama.cpp is a project for LLM inference in C/C++ . Release b9551 is a build version from the llama.cpp project's GitHub releases, following the project's rapid development cycle where multiple releas
Automated lint: 47 errors, 12 warnings, 3 info
arXiv:2606.06034v1 Announce Type: cross Abstract: Matrix inversion in chunk-wise parallel linear attention is a major bottleneck for long-context modeling, particularly on NPUs, where forward-substitu
arXiv:2606.06011v1 Announce Type: new Abstract: In this work, we propose a framework that combines multi-agent reinforcement learning (MARL) with model-based control to achieve safe, dynamically feasi
arXiv:2606.04746v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) algorithms are increasingly used to plan motion for robot teams in industrial warehouses and robotic shared workspaces,
its been such fun befriending Pari and seeing him completely reinvent his company for the agentic era, WHILE having the most insanely stacked customer base I've ever seen in the hardest engineering do
arXiv:2606.04582v1 Announce Type: cross Abstract: Real-time monitoring of the temperature distribution within components and sub-structures is a challenging topic in many systems due to restrictions o
At Google Cloud, our goal is to let you run large-scale analytical and data science workloads with maximum efficiency so you can process big data pipelines, machine learning, and ETL tasks. We recentl
arXiv:2606.03675v1 Announce Type: new Abstract: Methane is a potent greenhouse gas, and detecting leaks early via hyperspectral satellite imagery can help climate change mitigation efforts. Meanwhile,
The search results show general llama.cpp information and references to other recent builds (like b9484), but the specific details for b9487 were not clearly accessible. Based on the context from llam
arXiv:2606.03557v1 Announce Type: new Abstract: As generative AI capabilities expand, AI-driven virtual worlds face a growing architectural challenge. Users interact through in-world interfaces in mul
arXiv:2602.20217v2 Announce Type: replace-cross Abstract: Self-speculative decoding (SSD) accelerates LLM inference by skipping layers to create an efficient draft model, yet existing methods often re
arXiv:2606.00130v1 Announce Type: cross Abstract: We study Automatically Differentiable Nonlinear Tensor Networks (ADNTNs), a family of structured weight generators whose compact core tensors are trai