Search: “context”

arXiv:2608.22008v1 Announce Type: new Abstract: Disorientation is a common and distressing experience for people living with dementia. It often manifests as confusion about time, place, or personal co

arXiv:2608.23475v1 Announce Type: new Abstract: As large language models are increasingly used in data-scarce and evolving task scenarios, few-shot in-context learning (ICL) has become a key paradigm

arXiv:2608.22974v1 Announce Type: new Abstract: Large language model (LLM) agents rely heavily on knowledge encoded in model parameters or presented as unstructured context. In domain-specific tasks,

arXiv:2608.20566v1 Announce Type: new Abstract: AI agents extend large language models from single prompt-response interactions to long-running, goaldirected workflows that issue many model calls, inv

arXiv:2608.20661v1 Announce Type: new Abstract: Enterprise adoption of large language models in finance is constrained less by fluency than by trust: in Financial Planning and Analysis (FP&A) and othe

arXiv:2608.20830v1 Announce Type: cross Abstract: Evaluating mobility interventions at tourist destinations requires predicting visitor behavior under varying conditions. Traditional methods struggle

arXiv:2608.21107v1 Announce Type: new Abstract: Large Language Models (LLMs) are moving from code completion toward repository-scale agents that retrieve context, edit files, execute tools, and partic

arXiv:2608.21133v1 Announce Type: new Abstract: Medical image-text data can expose protected health information (PHI) through both visible image content as well as accompanying text, creating a barrie

arXiv:2608.21209v1 Announce Type: new Abstract: The rise of agentic AI enables LLMs to access diverse user data, raising critical privacy concerns. Prior work on contextual privacy studies whether LLM

I ran the Aider benchmark on Qwen 3.8 27B FP8 with FP8 KV cache 256K context vLLM. The score: 72.9 This matches Gemini 2.5 Pro from 2025-04-12 which also scored 72.9. Beats Claude Opus 4 from 2025-05-

With vision enabled I am able to run at 150k context on a single RTX 3090 and the results are just amazing. I was even able to write a gmail plugin for DeepSeek harness with locally hosted Qwen 3.8 27

arXiv:2512.00418v3 Announce Type: replace-cross Abstract: Significant Others (SOs) stabilize identity, regulate emotion, and support narrative meaning-making, yet many people today lack access to such

WARNING: I think I made a mistake with omlx, and its results below seem to be without any kind of acceleration. I am rerunning them with Lightning MTP and ANE support for prefill. Will update the post

Prior to Fable, it felt silly to waste too much time improving your coding harness or context strategies. A new model would arrive at the same price (or cheaper!) and paper over most of your problems.

Hello, So I've been trying lots of combinations in that never-ending landscape of options and settings. I wanted a proper quant of 3.8 27B running as fast as possible on my 5090 at 400W, with vision a

The latest RAG trend for the current agent harnesses (Codex, Cowork) is to do two passes of document processing to solve a knowledge work task over a data room of documents: 1️⃣ A fast and light pass,

Context: Earlier, open-source large models like Mimo V2.5 Pro, DeepSeek V4 Pro (first version), and Kimi K2.5 used to struggle with this prompt, and Qwen 3.6 27B couldn't even render the globe properl

Good afternoon, everyone! I wanted to show the work I've been doing around porting Ninfer over to the CMP170HX (Github) So, first, I do want to call out the amazing work that Neroued, Sergiuszm and sp

New/Old benchmark that provides a lot of answers for local LLM. I present to you a new test that I developed somewhat by accident: https://huggingface.co/cHunter789/Qwen3.8-27B-i1-IQ4_KS_KT-GGUF/tree/

Brace yourselves. We just entered a new era of frontier multimodal models. DeepSeek-V4-Flash-Vision-Exp advances multimodal agent performance. Also, pay attention to Ox Alpha 1M token contexts with te

arXiv:2608.19652v1 Announce Type: new Abstract: As LLM-based agents are deployed for longer and higher-stakes tasks, their memory systems continue to have crucial gaps. While existing memory benchmark

Welcome to the first Cloud CISO Perspectives for August 2026. Today, Chris Betz explains why the AI era makes it more important than ever to lean into security fundamentals.As with all Cloud CISO Pers

arXiv:2608.19950v1 Announce Type: cross Abstract: Artificial intelligence (AI) systems are increasingly used across domains to provide personalized information, recommendations, and decision support.

arXiv:2401.07468v4 Announce Type: replace-cross Abstract: The proposed model, CarSpeedNet, estimates scalar vehicle speed from a window of three-axis smartphone acceleration, without gyroscope, wheel-

I recently saw someone complaining that opencode causes compactions way too early (with 30k tokens still left). I fixed this issue and I thought I'd share my config to see if it helps anyone. I know p

Input tokens are often a meaningful part of the cost of running Retrieval Augmented Generation (RAG) at scale. This post describes a query-aware context compression pattern on Amazon Bedrock: after re

arXiv:2608.18305v1 Announce Type: new Abstract: X-ray fluorescence (XRF) microscopy maps elemental distributions, while optical microscopy can provide complementary morphological context. Localizing X

AirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card — without quantization, distillation, or pruning. You can even run 405B Llama 3.1 on

Learn how to add context-aware security monitoring to FHIR APIs using Amazon Bedrock. This post shows how to detect anomalous access patterns, classify data sensitivity automatically, and generate com

arXiv:2608.18590v1 Announce Type: new Abstract: Compact object detectors are suitable for resource-constrained visual perception, but their limited representation capacity creates an accuracy gap rela

arXiv:2608.18581v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) encode rich factual knowledge in their parameters, reliably recalling and verifying such knowledge remains a key

arXiv:2608.18968v1 Announce Type: new Abstract: Localized image edits can change a photograph's meaning while leaving most of it authentic, so forensic analysis must identify where an edit occurred. W

We are thrilled to announce that Google has been recognized as a Leader for the third year in a row in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms (CNAP). We believe this

Seeing a hype wave around GEN-1.5, and rightfully so. Lots of respect to Pete & Andy for executing so well. The secret is in the naturally repetitive motions in human-collected data. There're 2 main s

Very interesting new work Amazon and colleagues. (bookmark it) This connects to the emerging theme of treating the corpus as part of the harness. Planning loops, tool protocols, and context management

arXiv:2602.19816v3 Announce Type: replace-cross Abstract: For computational efficiency, modern language models are typically trained on independently sampled fixed-length sequences. Symbolic music lan

arXiv:2608.18661v1 Announce Type: new Abstract: Streaming text-to-speech is essential for low-latency spoken dialogue systems, yet many systems wait for sentence-level text and are therefore only pseu

arXiv:2608.17919v1 Announce Type: cross Abstract: Background and Context: Question and inquiry are integral parts of knowledge seeking and learning. Despite their importance, students tend not to ask

arXiv:2608.17911v1 Announce Type: new Abstract: As LLM agents operate across structured workflows and sessions, preserving long-term history does not ensure that later contexts can recover relevant ev

arXiv:2608.16919v1 Announce Type: cross Abstract: Recent advances in large language models and agent-based recommendation frameworks have introduced new opportunities for more flexible and context-awa

For over a decade, the Apache Hive Metastore (HMS) has served as the de facto metadata authority for big data analytics. Whether it was deployed on Hadoop clusters, self-managed Compute Engine VMs bac

Hello everyone, tried so hard to optimize my config and finally I simply get up to 70 t/s with q6 variant. And wanted to share with you guys so that other people with the same setup can enjoy. Please

arXiv:2608.17393v1 Announce Type: new Abstract: Reinforcement learning for coding agents increasingly relies on long-running agent harnesses to manage tool integration, repository contexts, and execut

arXiv:2608.17605v1 Announce Type: cross Abstract: Conversational AI is moving beyond isolated text prompts toward sustained, multimodal interaction. In real conversations, users clarify goals, revise

arXiv:2608.17304v1 Announce Type: cross Abstract: Formal verification is a crucial technique for ensuring the functional correctness of hardware designs. In the context of property checking, a key cha

arXiv:2608.16984v1 Announce Type: cross Abstract: Recent monocular depth estimators achieve strong zero-shot generalization, yet often struggle to preserve fine-grained structures and object boundarie