Knowledge catalogue
arXiv:2605.02525v1 Announce Type: new Abstract: Autonomous indoor mobile robots can navigate reliably to metric coordinates using established frameworks such as ROS 2 Navigation 2, yet they lack the a
arXiv:2602.13595v2 Announce Type: replace Abstract: Neural scaling laws provide a predictable recipe for AI advancement: reducing numerical precision should linearly improve computational efficiency a
arXiv:2605.02262v1 Announce Type: cross Abstract: Recently, video language models (VLMs) have been applied in various fields. However, the visual token sequence of the VLM is too long, which may cause
arXiv:2604.27476v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong applicability in edge industrial applications, yet their deployment remains severely constrained
arXiv:2604.27004v1 Announce Type: cross Abstract: We propose EdgeSpike, a co-designed spiking neural network (SNN) framework for autonomous low-power sensing in edge Internet of Things (IoT) architect
arXiv:2604.24916v1 Announce Type: new Abstract: We introduce asRoBallet, to the best of our knowledge, the first successful deployment of reinforcement learning (RL) on a humanoid ballbot hardware. Hi
Clement Delangue, CEO of Hugging Face, posted about receiving a piece of hardware that fits alongside a DGX Spark system, likely referring to an AI accelerator or GPU device. The post suggests a perso
arXiv:2604.23858v1 Announce Type: new Abstract: Video generation, while capable of generating realistic videos, is computationally expensive and slow, prohibiting real-time applications. In this paper
arXiv:2604.22293v1 Announce Type: cross Abstract: Lookup-table (LUT) based neural networks can deliver ultra-low latency and excellent hardware efficiency on FPGAs by mapping arithmetic operations dir
DAVIS, APRIL 25, 2026 — InferenceX has added DeepSeekv4 for @vllm_project 's day 0 support for GB200 disagg! Great work to @flowpow123 @rogerw0108 @NVIDIAAIDev @inferact for the fast support and engin
arXiv:2604.20129v1 Announce Type: new Abstract: The Synergistic Collapse occurs when scaling beyond 100 agents causes superlinear performance degradation that individual optimizations cannot prevent.
arXiv:2604.20568v1 Announce Type: new Abstract: Modeling high-dimensional dependencies while keeping likelihoods tractable remains challenging. Classical vine-copula pipelines are interpretable but ca
'Funny and distressingly realistic...propelled by awesome characters and inventive twists”— @andyweirauthor Silicon Valley invents the time machine in my upcoming book PARADOX INC, now available for p
arXiv:2604.19129v1 Announce Type: new Abstract: Existing facial reenactment methods struggle with a trade-off between expressiveness and fine-grained controllability. Holistic facial reenactment model
arXiv:2604.18610v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but incur substantial computational overhead and energy consumption during
Mark Gurman / Bloomberg: A look at Apple's management changes and several key executives' futures; sources say Mike Rockwell has considered leaving or taking an advisory role next year — John Ternus,
arXiv:2604.18348v1 Announce Type: new Abstract: Video diffusion transformers (DiTs) suffer from prohibitive inference latency due to quadratic attention complexity. Existing sparse attention methods e
Remember when Framework made the first laptop where you can easily upgrade its entire internal video card in three minutes flat? The company's getting into the external graphics game, too. As promised
arXiv:2603.19830v2 Announce Type: replace Abstract: Efficient structural perception is essential for mapping and autonomous navigation on resource-constrained robots. Existing 3D methods are computati
arXiv:2604.15665v1 Announce Type: new Abstract: Markerless 3D movement analysis from monocular video enables accessible biomechanical assessment in clinical and sports settings. However, most research
One of the most mortifying things about knowing a lot of techies is listening to them tell me excitedly about some very important discovery that they believe they have made. Recently, I ran into an ac
arXiv:2604.15357v1 Announce Type: cross Abstract: Precise estimation of model inference latency is crucial for time-critical mobile edge applications, enabling devices to calculate latency margins aga
arXiv:2511.00739v3 Announce Type: replace Abstract: Agentic AI serving converts monolithic LLM-based inference to autonomous problem-solvers that can plan, call tools, perform reasoning, and adapt on
At SemiAnalysis, we're quite tired of the minimalist style webapps and landing pages that have become so commonplace lately. Today, we're introducing Minecraft mode on inferencex dot com so that you c
arXiv:2604.13662v1 Announce Type: cross Abstract: Tuning of gate-defined semiconductor quantum dots (QDs) is a major bottleneck for scaling spin qubit technologies. We present a deep learning (DL) dri
Vultr offers preemptible cloud instances powered by AMD Instinct GPUs, providing a cost-effective option for running GPU-accelerated workloads such as AI/ML training, inference, and high-performance c
arXiv:2604.12798v1 Announce Type: cross Abstract: FlashAttention-style online softmax enables exact attention computation with linear memory by streaming score tiles through on-chip memory and maintai
arXiv:2604.09611v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in applications forming multi-request workflows like document summarization, search-based copilots,
arXiv:2511.09376v2 Announce Type: replace Abstract: SHapley Additive exPlanations (SHAP) is a key tool for interpreting decision tree ensembles by assigning contribution values to features. It is wide
arXiv:2509.08193v2 Announce Type: replace-cross Abstract: We present FlexiFlow, a lifetime-aware design framework for item-level intelligence (ILI) where computation is integrated directly into dispos
arXiv:2604.11090v1 Announce Type: new Abstract: Simulation trained legged locomotion policies often exhibit performance loss on hardware due to dynamics discrepancies between the simulator and the rea
arXiv:2608.08256v1 Announce Type: new Abstract: Pretrained Transformer encoders such as AraBERT, MARBERT, and CAMeLBERT have become the standard backbone for Arabic natural language understanding, but
arXiv:2608.08761v1 Announce Type: cross Abstract: In an era defined by escalating climate change and the pervasive deployment of edge intelligence, the environmental cost of semiconductor manufacturin
arXiv:2607.18171v2 Announce Type: replace Abstract: Real-time multimodal applications, including voice agents and interactive video generation, compose heterogeneous models into pipelines whose effici
arXiv:2608.08287v1 Announce Type: new Abstract: GPU language comparisons are almost always run on tiled dense linear algebra, where every toolchain is good and the differences are small. We implement
arXiv:2608.06412v1 Announce Type: cross Abstract: Understanding which surfaces in a scene are physically accessible to a given tool is fundamental for robotic interaction, yet 3D perception systems ty
Most enterprises connect with their customers through a device. Whether it’s using a mobile app to order a product, contact customer service, view content, or manage their account, the customer experi
arXiv:2608.05033v1 Announce Type: cross Abstract: Sparse matrix kernels are fundamental to scientific computing, graph analytics, and machine learning. Their GPU performance depends strongly on the in
arXiv:2602.14010v2 Announce Type: replace-cross Abstract: Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image anal
arXiv:2608.00859v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions parameterized by multiple basis coefficients. This in
arXiv:2608.01615v1 Announce Type: cross Abstract: We present a set of tools for mapping general stochastic programs to thermodynamic hardware designed for energy-efficient stochastic sampling. Given a
I've been out of these forums for awhile but I figured I would provide a formal update on how this has been going now that it has some operation time under its belt, just to put the information out th
Ran DeepSeek V4-Flash-0731 — the full official checkpoint, not a re-quant — on commodity used hardware. Sharing because I couldn't find anyone else publishing Ampere results for this engine. Why bothe
arXiv:2607.28848v1 Announce Type: cross Abstract: LLM serving systems are provisioned for peak load to meet strict latency targets, leaving substantial GPU compute idle whenever traffic falls below pe
A combined architecture using KAI Scheduler and vCluster enables multiple teams to run fully isolated Kubernetes tenant clusters on a shared GPU node, each with its own control plane, RBAC, CRDs, and
arXiv:2607.28633v1 Announce Type: cross Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly. When prefill and decode run on separate
Vivid depiction of a dark scenario for Nvidia. “Indeed, CEO Jensen Huang has been so aggressive in funding the AI ecosystem that the company is functioning almost like a bank; with annual free cash fl
The article shows that dense‑attention performance in long‑context inference is governed by group size (query heads per KV head), head dimension, and sequence length, with prefill being compute‑bound
arXiv:2607.28416v1 Announce Type: new Abstract: Curved tactile fingertips for dexterous manipulation must resolve fine contact geometry, distinguish normal and tangential loads, and capture transient
arXiv:2607.27231v1 Announce Type: cross Abstract: Large language models (LLMs) have significantly increased the demand for efficient accelerator kernels, but kernel development remains a highly specia
arXiv:2607.28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale. In pra
arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver
NVIDIA **nvmath‑python v1.0** is a Python library that wraps CUDA‑X and NVPL math libraries (cuFFT, cuBLASLt, cuDSS, cuSPARSE, cuTENSOR, cuBLASMp) to give NumPy, CuPy, and PyTorch users GPU‑accelerate
arXiv:2607.25593v1 Announce Type: new Abstract: Robotic hardware evolves over time, but demonstration data is often tied to a specific sensor and actuator configuration. This raises a practical and un
arXiv:2607.24148v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deploy
arXiv:2607.24741v1 Announce Type: cross Abstract: Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distri
arXiv:2607.24313v1 Announce Type: cross Abstract: Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data fr
arXiv:2607.22869v1 Announce Type: cross Abstract: Monte Carlo tree search (MCTS) enables artificial intelligence (AI) decision-making, but requires 55-300 W on conventional processors, limiting edge d
arXiv:2607.22714v1 Announce Type: cross Abstract: Real-time perception is a foundational requirement for advanced driver assistance systems (ADAS) and autonomous vehicles, yet embedded automotive plat
arXiv:2607.23389v1 Announce Type: cross Abstract: Conventional CAPTCHAs pose puzzles that modern AI systems increasingly solve, while behavioral and cryptographic-attestation defenses carry privacy or