Search: “inference”

arXiv:2510.04800v3 Announce Type: replace Abstract: Recent progress in large language models demonstrates that hybrid architectures--combining self-attention mechanisms with structured state space mod

arXiv:2604.19536v1 Announce Type: new Abstract: Recent navigation systems achieve strong benchmark results, yet real-world deployment often remains visibly stop-and-go. This bottleneck arises because

This post likely demonstrates running Qwen2 3.6B or 27B model in GGUF format using llama-server with default specifications, showcasing inference capabilities of quantized open-source models. The comm

arXiv:2604.19679v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers (DiTs) have enabled high-quality joint audio-video generation, producing videos with synchronized audio within

Q1 2026 Shareholder Update https://ir.tesla.com/#quarterly-disclosure We continued to make meaningful progress on the build out of the infrastructure & AI software that underpins our Robotaxi & future

arXiv:2512.19442v3 Announce Type: replace-cross Abstract: Diffusion-based generative models have greatly impacted the speech processing field in recent years, exhibiting high speech naturalness and sp

arXiv:2604.19144v1 Announce Type: new Abstract: Recent years have witnessed growing interest in applying Large Reasoning Models (LRMs) to Machine Translation (MT). Existing approaches predominantly ad

arXiv:2510.17925v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at code-related tasks but often struggle in realistic software repositories, where project-specific APIs an

arXiv:2510.24738v2 Announce Type: replace-cross Abstract: Running offers substantial health benefits, but improper gait patterns can lead to injuries, particularly without expert feedback. While prior

arXiv:2604.19295v1 Announce Type: new Abstract: Test-time training (TTT) adapts model parameters on unlabeled test instances during inference time, which continuously extends capabilities beyond the r

Kimi K2.6 is now available for use on Together AI's cloud platform, which offers AI model deployment and inference services. This announcement indicates the model has been added to Together AI's roste

arXiv:2604.19473v1 Announce Type: new Abstract: Generating high-quality videos from complex temporal descriptions that contain multiple sequential actions is a key unsolved problem. Existing methods a

Google announced Ironwood, its seventh-generation TPU that is twice as power efficient as the previous generation, alongside specialized hardware designed to support the emerging agentic AI era. Ironw

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

arXiv:2510.16458v2 Announce Type: replace Abstract: Natural Language Inference (NLI) datasets often exhibit human label variation. To better understand these variations, explanation-based approaches a

arXiv:2507.20993v3 Announce Type: replace Abstract: We study how to learn treatment policies from multimodal electronic health records (EHRs) that consist of tabular data and clinical text. These poli

arXiv:2604.18194v1 Announce Type: cross Abstract: Drifting Models [Deng et al., 2026] train a one-step generator by evolving samples under a kernel-based drift field, avoiding ODE integration at infer

Release b8869 is a version update for llama.cpp, a C/C++ library for LLM inference . This is one of many rapid incremental releases in the llama.cpp project's development cycle, following the pattern

B8875 is a release of llama.cpp, a C/C++ implementation for LLM inference . The llama.cpp project does not follow traditional release practices, with multiple releases published in a single day . This

arXiv:2604.16514v1 Announce Type: new Abstract: Autoregressive vision-language models (VLMs) deliver strong multimodal capability, but their token-by-token decoding imposes a fundamental inference bot

arXiv:2502.10605v3 Announce Type: replace-cross Abstract: Estimating the causal effects of interventions is crucial to policy and decision-making, yet outcome data are often missing or subject to non-

arXiv:2604.16368v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by using a small draft model to propose k candidate tokens for a target model to verify. While effective

arXiv:2604.16483v1 Announce Type: new Abstract: Concept erasure in Text-To-Image (T2I) diffusion models is vital for safe content generation, but existing inference-time methods face significant limit

arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli

arXiv:2604.17087v1 Announce Type: new Abstract: Recent Multimodal Large Language Models (MLLMs) have demonstrated strong performance on vision-language understanding tasks, yet their inference efficie

arXiv:2511.17171v4 Announce Type: replace Abstract: Predicting wildfire risk is a reasoning-intensive spatial problem that requires the integration of visual, climatic, and geographic factors to infer

arXiv:2604.17277v1 Announce Type: new Abstract: Physical neural networks offer a transformative route to edge intelligence, providing superior inference speed and energy efficiency compared to convent

arXiv:2604.17283v1 Announce Type: new Abstract: User preferences evolve across months of interaction, and tracking them requires inferring when a stated preference has been changed by a subsequent lif

arXiv:2604.17935v1 Announce Type: new Abstract: The key-value (KV) cache is the dominant memory bottleneck during Transformer inference, yet little is known theoretically about how aggressively it can

arXiv:2510.02370v3 Announce Type: replace Abstract: Large language models leverage both parametric knowledge acquired during pretraining and in-context knowledge provided at inference time. Crucially,

arXiv:2604.17310v1 Announce Type: new Abstract: Discrete diffusion models form a powerful class of generative models across diverse domains, including text and graphs. However, existing approaches fac

arXiv:2604.18509v1 Announce Type: new Abstract: Large language models (LLMs) are widely used in retrieval-augmented generation (RAG) to incorporate external knowledge at inference time. However, when

arXiv:2604.16518v1 Announce Type: new Abstract: Satellite constellations are transforming space systems from isolated spacecraft into networked, software-defined platforms capable of on-orbit percepti

arXiv:2604.17690v1 Announce Type: cross Abstract: Reconfigurable intelligent surfaces (RISs) modify signal reflections to enhance wireless communication capabilities. Classical RIS phase optimization

arXiv:2604.16734v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have recently demonstrated strong capabilities in understanding and generating responses from diverse visual in

arXiv:2509.01082v3 Announce Type: replace Abstract: Probabilistic programming offers a powerful framework for modeling uncertainty, yet statistical model discovery in this domain entails navigating an

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:2604.16434v1 Announce Type: cross Abstract: When a system commits to a hypothesis, much of the evidential structure behind that commitment is lost to compression. Standard accounts assume that s

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:2510.00546v5 Announce Type: replace Abstract: Large Reasoning Models (LRMs) allocate substantial inference-time compute to Chain-of-Thought (CoT) reasoning, improving performance on mathematics,

We are entering an extremely exciting era for open-weight models. Kimi K2.6 now feels like a top agentic model. I took it for a spin via @FireworksAI_HQ fast inference APIs. Kimi K2.6 has impressive a

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

arXiv:2604.15611v1 Announce Type: cross Abstract: Latent diffusion models have emerged as powerful generative models in medical imaging, enabling the synthesis of high quality brain magnetic resonance

arXiv:2409.01794v2 Announce Type: replace-cross Abstract: In this paper we show how to exploit interventional data to acquire the joint conditional distribution of all the variables using the Maximum

arXiv:2604.15782v1 Announce Type: new Abstract: Traffic simulations, essential for planning urban transit infrastructure interventions, require vehicle-category-specific origin-destination (OD) data.

An MCP bridge project that enables integration between AI coding tools (Kiro, Claude, and Cursor) and local Ollama instances for offline model inference. The bridge facilitates communication between t