Search: “hardware”

arXiv:2511.21686v2 Announce Type: replace Abstract: Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sens

arXiv:2604.16722v1 Announce Type: new Abstract: Predicting full-field physics through the real-time virtual sensing of engineering systems can enhance limited physical sensors but often requires spars

arXiv:2604.17863v1 Announce Type: new Abstract: Spinning flexible objects, exemplified by traditional Chinese handkerchief performances, demands periodic steady-state motions under nonlinear dynamics

arXiv:2507.19205v2 Announce Type: replace Abstract: Real-time particle transverse momentum (p_T) estimation in high-energy physics demands algorithms that are both efficient and accurate under strict

arXiv:2604.16779v1 Announce Type: cross Abstract: Quantum feature maps offer expressive embeddings for classical learning tasks, and augmenting sparse identification of nonlinear dynamics (SINDy) with

arXiv:2604.18026v1 Announce Type: new Abstract: Many deployed systems expose black-box objectives whose minimizing configuration shifts with an externally observed context. When contexts revisit a sma

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

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:2604.16883v1 Announce Type: new Abstract: In long-context decoding for LLMs and LMMs, attention becomes increasingly memory-bound because each decoding step must load a large amount of KV-cache

arXiv:2604.16429v1 Announce Type: cross Abstract: We introduce Mosaic, a probabilistic weather forecasting model that addresses two principal sources of spectral degradation in ML-based weather predic

arXiv:2604.16913v1 Announce Type: cross Abstract: Decentralized Autonomous Organizations (DAOs) are inclined explore Small Language Models (SLMs) as edge-native constitutional firewalls to vet proposa

arXiv:2604.16887v1 Announce Type: new Abstract: Robotic manipulators for aerospace applications require a delicate balance between lightweight construction and fault-tolerant operation to satisfy stri

arXiv:2602.09130v3 Announce Type: replace Abstract: Model compression is increasingly essential for deploying large language models (LLMs), yet existing comparative studies largely focus on pruning an

We're open-sourcing FlashKDA — our high-performance CUTLASS-based implementation of Kimi Delta Attention kernels. Achieves 1.72×–2.22× prefill speedup over the flash-linear-attention baseline on H20,

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

A sophomore engineering student built a platform, landed corporate sponsors, and started a company. In three weeks. 🚀🤯 Engineering students have no way to build in public and get noticed by companies.

arXiv:2503.18970v3 Announce Type: replace Abstract: Structured State Space Models (SSMs) have emerged as a transformative paradigm in sequence modeling, addressing critical limitations of Recurrent Ne

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 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

arXiv:2604.15821v1 Announce Type: cross Abstract: Universal Machine Learning Interatomic Potentials (uMLIPs), pre-trained on massively diverse datasets encompassing inorganic materials and organic mol

arXiv:2604.16201v1 Announce Type: cross Abstract: Consumer LiDARs in mobile devices and robots typically output a single depth value per pixel. Yet internally, they record full time-resolved histogram

arXiv:2604.15911v1 Announce Type: new Abstract: Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains co

arXiv:2604.15977v1 Announce Type: new Abstract: M-MIMO is one of the crucial technologies for increasing spectral and energy efficiency of wireless networks. Most of the current works assume that M-MI

arXiv:2604.15363v1 Announce Type: cross Abstract: Motivated behaviour relies on the brain's capacity to evaluate effort and reward. Dysregulation within these processes contributes to a spectrum of co

arXiv:2604.15618v1 Announce Type: new Abstract: We investigate Functional Majority Voting (FMV), a method based on functional consensus for code generation with Large Language Models, which identifies

arXiv:2604.15714v1 Announce Type: cross Abstract: Always-on converter health monitoring demands sub-mW edge inference, a regime inaccessible to GPU-based physics-informed neural networks. This work se

Qiskit v2.4 represents the latest release of IBM's open-source quantum computing framework, introducing new features and improvements to the software development kit for quantum programming. The relea

arXiv:2503.05578v4 Announce Type: replace Abstract: Pose estimation-guided unseen object 6-DoF robotic manipulation is a key task in robotics. However, the scalability of current pose estimation metho

arXiv:2604.16119v1 Announce Type: new Abstract: Multivariate time series classification (MTSC) plays a crucial role in various domains, including biomedical signal analysis and motion monitoring. Howe

arXiv:2604.15375v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown significant improvement in RTL code generation. Despite the advances, the generated code is often riddled with

b8841 is a release of llama.cpp dated April 18, 2026 , a C/C++ library for large language model inference. The main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art

B8846 is a release version of llama.cpp, a C/C++ inference engine for running large language models locally. The release includes pre-built binaries and libraries for multiple platforms including macO

b8848 is a release from llama.cpp, an open-source C/C++ project for LLM inference . This release builds on the rapidly-developing codebase with regular updates that include bug fixes, feature improvem

b8850 is a release of llama.cpp that includes CUDA refactoring for AMD matrix multiplication acceleration, with fixes for CDNA and RDNA3 GPU architectures . The release provides precompiled binaries a

The llama.cpp project is the main playground for developing new features for the ggml library , and the main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art perfor

Release b8838 is a version of llama.cpp, a C/C++ implementation for LLM inference. The release likely contains bug fixes, performance improvements, and updates to the codebase for running large langua

EditAnything IC-LoRA is a unified control adapter trained on LTX-2.3-22b that enables multiple control signals for video generation, allowing fine-grained video-to-video control on top of text-to-vide

Okay this one is insane. A new 18B frankenstein model was just released on @huggingface — Beats the new Qwen3.6-35B-A3B on a 44-test suite despite requiring 12GB VRAM instead of 24GB 🤯 Runs on a SINGL

arXiv:2511.15915v2 Announce Type: replace-cross Abstract: We present AccelOpt, a self-improving large language model (LLM) agentic system that autonomously optimizes kernels for emerging AI acclerator

arXiv:2604.14655v1 Announce Type: cross Abstract: We present AgentGA, a framework that evolves autonomous code-generation runs by optimizing the agent seed: the task prompt plus optional parent archiv

b8824 is a llama.cpp release that optimizes HMX matmul operations, including refactoring functions to use size_t for tile counts and improving readability of core matrix multiplication routines. Relea

Release b8831 of llama.cpp includes CI improvements for Android ARM64 build and release, along with a fix for the server to respect the ignore EOS flag. The release provides compiled binaries for mult

Release b8833 of llama.cpp includes updates to the ggml-webgpu backend, fixing compiler warnings and refactoring FlashAttention encoding, along with workflow improvements and precision adjustments for

arXiv:2604.15013v1 Announce Type: new Abstract: Data-driven dexterous hand manipulation requires large-scale, physically consistent demonstration data. Simulation and video-based methods suffer from s