Search: “llm”

arXiv:2604.06485v1 Announce Type: cross Abstract: 'Best-of-N' selection is a popular inference-time scaling method for code generation using Large Language Models (LLMs). However, to reliably identify

arXiv:2503.08292v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly applied to outpatient referral tasks across healthcare systems. However, there is a lack of stan

LiteParse hit 4K+ GitHub stars in 3 weeks. ~500 pages in 2 seconds. No GPU. No API keys. 50+ file formats. Now @LoganMarkewich, our Head of Open Source, will show you how to build with it. Live worksh

arXiv:2506.18841v3 Announce Type: replace-cross Abstract: Ultra-long generation by large language models (LLMs) is a widely demanded scenario, yet it remains a significant challenge due to their maxim

arXiv:2604.08333v1 Announce Type: new Abstract: The rise of multimodal large language models (MLLMs) has sparked an unprecedented wave of applications in the field of medical imaging analysis. However

The Mac Mini M4 Pro with 48GB unified memory is a popular choice in the local AI community for running large language models via Ollama, as its Apple Silicon architecture makes all 48GB of RAM dire...

arXiv:2509.22750v3 Announce Type: replace Abstract: Real-world multi-hop QA is naturally linked with ambiguity, where a single query can trigger multiple reasoning paths that require independent resol

arXiv:2604.06505v1 Announce Type: cross Abstract: Large language models (LLMs) are widely explored for reasoning-intensive research tasks, yet resources for testing whether they can infer scientific c

arXiv:2604.04771v2 Announce Type: replace-cross Abstract: Current document parsing methods advance primarily through model architecture innovation, while systematic engineering of training data remain

arXiv:2604.07085v1 Announce Type: new Abstract: In electronic health records (EHRs), clustering patients and distinguishing disease subtypes are key tasks to elucidate pathophysiology and aid clinical

arXiv:2604.07747v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) can improve low-k reasoning accuracy while narrowing solution coverage on challenging math que

arXiv:2509.23322v2 Announce Type: replace Abstract: With the continuous expansion of Large Language Models (LLMs) and advances in reinforcement learning, LLMs have demonstrated exceptional reasoning c

arXiv:2604.06798v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) based large language models (LLMs) offer strong performance but suffer from high memory and computation costs. Weight binariz

arXiv:2411.19121v2 Announce Type: replace-cross Abstract: While text-to-video diffusion models have advanced significantly, creating coherent long-form content remains unreliable due to stochastic sam

arXiv:2604.03336v2 Announce Type: replace Abstract: BitNet b1.58 (Ma et al., 2024) demonstrates that large language models can operate entirely on ternary weights {-1, 0, +1}, yet no native binary wir

One great outcome of PaperWiki is personalized surveys. Survey papers continue to be one of the best ways to track a field. My agents are now generating personalized surveys on topics using my paper L

arXiv:2604.07788v1 Announce Type: cross Abstract: We introduce PeReGrINE, a benchmark and evaluation framework for personalized review generation grounded in graph-structured user--item evidence. PeRe

arXiv:2604.08499v1 Announce Type: cross Abstract: Prompt injection attacks pose serious security risks across a wide range of real-world applications. While receiving increasing attention, the communi

arXiv:2604.06228v1 Announce Type: cross Abstract: We introduce probabilistic language tries (PLTs), a unified representation that makes explicit the prefix structure implicitly defined by any generati

arXiv:2505.24499v2 Announce Type: replace Abstract: Generating high-quality Scalable Vector Graphics (SVGs) is challenging for Large Language Models (LLMs), as it requires advanced reasoning for struc

arXiv:2604.06811v1 Announce Type: cross Abstract: Skill-based agent systems tackle complex tasks by composing reusable skills, improving modularity and scalability while introducing a largely unexamin

arXiv:2603.04759v2 Announce Type: replace Abstract: The limited context window of contemporary large language models (LLMs) remains a primary bottleneck for their broader application across diverse do

arXiv:2604.07415v1 Announce Type: cross Abstract: Large language models (LLMs) are probabilistic in nature and perform more reliably when augmented with external information. As complex queries often

arXiv:2604.07101v1 Announce Type: cross Abstract: We present the Surveillance Forgery Image Test Range (SurFITR), a dataset for surveillance-style image forgery detection and localisation, in response

arXiv:2604.07513v1 Announce Type: cross Abstract: AI-based persona simulation -- often referred to as digital twin simulation -- is increasingly used for market research, recommender systems, and soci

arXiv:2509.09794v4 Announce Type: replace Abstract: Computational models have emerged as powerful tools for multi-scale energy modeling research at the building and urban scale, supporting data-driven

The challenge with agent harnesses is not only building them but distribution. If we want agent products to scale like saas, the interfaces and ecosystem still need a fundamental breakthrough. im exci

The Information wrote that Meta consumes 60.2T tokens per month, or ~750M per employee. Meta is getting absolutely token-mogged by us currently. SemiAnalysis employees consume 1.86B tokens per month.

The power of JAX Introducing gyaradax 🐉: A JAX solver for local flux-tube gyrokinetics with custom CUDA kernels for acceleration. This entire code was vibecoded by @ggalletti_ and me in a month. Valid

arXiv:2604.06621v1 Announce Type: cross Abstract: Dr. David Blackwell was a mathematician and statistician of the first rank, whose contributions to statistical theory, game theory, and decision theor

When using Ollama Pro's cloud models with OpenClaw, a local Ollama installation is not strictly required — OpenClaw is an AI agent execution layer that handles tools, memory, scheduling, and messa...

arXiv:2604.06205v1 Announce Type: cross Abstract: The growth of online platforms and user content requires strong content moderation systems that can handle complex inputs from various media types. Wh

arXiv:2510.12476v2 Announce Type: replace Abstract: Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this abi

arXiv:2604.08281v1 Announce Type: new Abstract: Large reasoning models (LRMs) have achieved strong performance enhancement through scaling test time computation, but due to the inherent limitations of

arXiv:2604.08032v1 Announce Type: cross Abstract: Automated maritime collision avoidance will rely on human supervision for the foreseeable future. This necessitates transparency into how the system p

wow. GenAI is definitely not living up to the hype, for most people. 🦔A global survey of 3,750 executives and employees found that 54% of workers bypassed their company's AI tools in the past 30 days

Wrapped up the 3-day AI Engineer conference in London. Key takeaways: Planning & verification > implementation. Humans define what to build and validate it works. AI handles the coding. The harness ma

(1/5) FP4 hardware is here, but 4-bit attention still kills model quality, blocking true end-to-end FP4 serving. To fix that, we propose Attn-QAT, the first systematic study of quantization-aware trai

Editor’s note: This blog post outlines Google Cloud’s GPU AI/ML infrastructure reliability strategy, and will be updated with links to new community articles as they appear. As we enter the era of mul

*AI Systems Performance Engineering* by Chris Fregly is a ~1,000-page book (published December 2025) covering GPU/CUDA kernel tuning, PyTorch optimization, distributed training, and high-throughput...

llama.cpp release **b8737** is a focused maintenance build that adds missing CUDA error handling to the ggml backend. Specifically, it checks the return values of NVIDIA CUB library calls used in t...

Compliance workflow automation startup Haast Pty Ltd. said today it has raised $12 million in an early-stage round of funding to help organizations accelerate the rollout of artificial intelligence-ge

I was unable to retrieve the specific X (Twitter) post at the URL provided, as the content is not accessible through search results. The tweet's text snippet ('memory is context, and context is wha...

🎙️Introducing Max Agency Max Agency is a new podcast where we go deep on how the best agents are actually being built: architecture decisions, tradeoffs, evals, and everything in between. Each episode

NEW paper from Microsoft Every agent benchmark has the same hidden problem: how do you know the agent actually succeeded? Microsoft researchers introduce the Universal Verifier, which discusses lesson

Nvidia published DWDP (Distributed Weight-Data Parallelism), a new inference parallelism strategy focused on prefill. It sounds slightly insane until you remember the target machine is GB200 NVL72. Th