Search: “rag”

When Retrieval Fails Before It Begins: Structurally Indirect Prerequisite Eviction as a Retention Failure in Agentic Memory

arXiv:2608.20400v1 Announce Type: new Abstract: Agentic memory under a fixed budget involves two stages: retention and retrieval. Existing retrieval-centered paradigms implicitly assume necessary evid

24 Aug 2026

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

When Trust Meets Truth: Trust-Truth Separability in LLM-as-Judge

DGX agent

arXiv:2608.21097v1 Announce Type: new Abstract: LLM-as-Judge systems can produce multi-dimensional evaluations, such as trustworthiness, reliability, and factuality, and these outputs are often interp

researcharxiv-cs-ai

24 Aug 2026

Has anyone actually made 64k feel like 300k+ with recursive local agents?

I'm running Qwen 3.8 27B locally on a single GPU. I can push the context to 131k, but I'd rather run it faster at 64k if the agent can manage context properly. What I have in mind is pretty simple: on

23 Aug 2026

Trying to optimize LLM inference latency — Ollama + OpenWebUI/AnythingLLM

Hi everyone, I'm currently working on optimizing an LLM setup at my company and I'm trying to identify where the actual performance bottleneck is. Our current setup is roughly: LLM: NVIDIA Nemotron mo

model-releasesr-ollama

23 Aug 2026

Local Ai

Gemax Ai New Version v1.9.15 (Offline AI Agent for Windows)

Gemax 1.9.15 — What’s new LAN server — share Gemax on your local network; open the real IP from another PC or phone Mobile-friendly UI — responsive layout for phone browsers on the same Wi‑Fi Workspac

local-air-ollama

22 Aug 2026

A Virtual Member of a Community of Practice for the Society of Petroleum Engineers: From Prototype to Deployment

arXiv:2608.19199v1 Announce Type: cross Abstract: We describe the evolution of a virtual assistant, called ATHENA, designed to support the capture, retrieval, and dissemination of knowledge for member

Llama.cpp DSpark PC Tree Fork (up to 3%-29.5% faster!)

Hello gang, I made an implementation of DSpark PC Tree (Parent conditioned drafting tree). This is an implementation of this research paper: https://arxiv.org/abs/2608.02123 Unaffiliated, just found i

Time-Series Retrieval for Grounding Multimodal Language Models in Remaining Useful Life

arXiv:2608.19218v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are increasingly being explored for domain-specific maintenance and prognostics tasks, raising the

Hardware

TorchDCM: A Unified PyTorch-Native Package for Discrete Choice Modeling

arXiv:2608.19231v1 Announce Type: cross Abstract: Estimating large and simulation-intensive discrete choice models (DCMs) requires repeated evaluation of utilities, probabilities, derivatives, and sim

hardwarearxiv-cs-lg

10 questions every startup should answer before moving to production with their AI prototype

model-releasesgoogle-cloud-ai

It’s never been easier to start an AI-powered startup on Google Cloud. You grab an API key from Google AI Studio at breakfast, paste it into Antigravity, and by lunch you’ll have a nascent prototype o

A Multi-Agent Platform for Automated Enterprise Analytics and Insight Generation

arXiv:2608.18740v1 Announce Type: new Abstract: This paper proposes a multi-agent framework built on CrewAI [1] for conversational business intelligence. Five specialized AI agents operate in a sequen

I pushed Qwen3.8-27B to 381 tps for a single request on a RTX 3090

Four days ago I released a hyper-optimized Qwen3.8-27B inference engine for an RTX 3090 (82 tps single request, 672 peak). Since then it went to ~114, then ~138 tps single-user with DFlash2 drafting a

One Gate Is Not Enough: Composing Stateful Pre-Action Controls for Agentic AI

arXiv:2608.18360v1 Announce Type: cross Abstract: Agentic AI systems take consequential actions governed by more than one pre-action control at once: authority, resource, and evidence gates that can a

Pedagogical AI in Mental Health: A Tri-Stream Fine-Tuned LLM Framework for Automated Clinical Supervision and Risk Triage

arXiv:2608.18438v1 Announce Type: cross Abstract: Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a 'supervision gap' where novice therapists manage high

PLASMA: A Layout-Aware Benchmark Reveals Memory Layout Matters for Graph-based ANNS on GPU

model-releasesarxiv-cs-cv

arXiv:2508.15436v2 Announce Type: replace-cross Abstract: We propose a extbf{P}latform for extbf{L}ayout-extbf{A}ware extbf{S}earch and extbf{M}emory extbf{A}rrangement (extbf{PLASMA}), a unified eval

rEDMRec: Distilling Large Language Model Reasoning into an Editable Experience Memory for Recommendation

arXiv:2608.18952v1 Announce Type: cross Abstract: Large language models can improve recommendation quality by reasoning explicitly over user history and candidate items - for example, extracting a use

SESSE: Sketch, Expand, Sort, Summarize, Evaluate -- LLM-as-Judge Evaluation via Structured Decomposition

arXiv:2608.18303v1 Announce Type: new Abstract: LLM-as-judge evaluation reduces response quality assessment to a single holistic A/B preference choice, providing no mechanism to isolate which quality

StocksTalk: A Voice-Enabled Conversational Agent for Structured Query Generation over Web Data

arXiv:2608.18105v1 Announce Type: cross Abstract: StocksTalk is a voice-enabled conversational system for transforming spoken financial screening requests into executable and validated structured quer

Authorization Before Context: A Model-Neutral Audience Boundary Against Cross-Audience Memory Leakage in Agentic Systems

arXiv:2608.17148v1 Announce Type: cross Abstract: A personal language agent learns a fact from one audience and may later place it in the prompt it assembles for another. This memory-to-context step i

D^2ACCI: A Dual-Loop Diagnostic Protocol for Evidence-Preserving Agent Memory

arXiv:2608.17756v1 Announce Type: new Abstract: Memory is a key capability of LLM agents. Persistent memory extends this across sessions---enabling recall, revision, and personalization. Yet its multi

Deep Academic Survey: Stateful Agentic Closed-Loop Paradigm for Academic Survey Automation

model-releasesarxiv-cs-cv

arXiv:2608.18034v1 Announce Type: new Abstract: Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coh

Do Large Language Models Play Six Degrees of Separation? Measuring Topological Compression in Long-Context Manifolds

arXiv:2608.17950v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable multi-hop reasoning capabilities over long contexts, yet the internal mechanisms enabling these dist

researcharxiv-cs-cl

GADR: Gathering Architecture Decision Records from Meeting Transcriptions

arXiv:2608.17694v1 Announce Type: cross Abstract: Existing LLM-based approaches to Architecture Decision Record (ADR) generation share a critical and largely unexamined assumption: that input is alrea

Tutorials

Intent-Driven Dynamic Chunking: Segmenting Documents to Reflect Predicted Information Needs

arXiv:2602.14784v1 Announce Type: cross Abstract: Breaking long documents into smaller segments is a fundamental challenge in information retrieval. Whether for search engines, question-answering syst

tutorialsarxiv-cs-ai

LLM Enhancement with Domain Expert Mental Model to Reduce LLM Hallucination with Causal Prompt Engineering

arXiv:2509.10818v2 Announce Type: replace Abstract: When consequential decisions depend on knowledge that exists nowhere in writing, LLMs hallucinate not from retrieval failure but from model absence.

MITRE-SAGE: A Multi-Agent Cybersecurity Question-Answering Model

model-releasesarxiv-cs-lg

arXiv:2608.16921v2 Announce Type: cross Abstract: Effective cybersecurity operations require timely and accurate analysis of large-scale heterogeneous security information; however, analysts increasin

Preference Is Not Intervention: The Structure and Stability Boundaries of Reader-Specific Evidence Utility

arXiv:2608.17781v1 Announce Type: new Abstract: ML systems increasingly condition decisions on downstream model identity, but this is useful only if model-specific differences form reusable structure

researcharxiv-cs-cl

VentureBeat names Rob Strechay as its first Lead Analyst, expanding its enterprise AI research push

model-releasesventurebeat-ai

Rob Strechay, until recently managing director and principal analyst at theCUBE Research, has joined VentureBeat as our first Lead Analyst and a founding analyst of VentureBeat Research. His arrival i

Applications

WIP: LLM Odyssey: A Game-Based Platform for Teaching LLM Engineering Concepts

arXiv:2608.16924v1 Announce Type: cross Abstract: This work-in-progress (WIP) innovative practice category paper presents LLM Odyssey, an open source, browser-based serious gaming platform comprising

applicationsarxiv-cs-ai

Automating the Detection of Requirement Dependencies Using Large Language Models

arXiv:2602.22456v2 Announce Type: replace-cross Abstract: Requirements are inherently interconnected through various types of dependencies. Identifying these dependencies is essential, as they underpi

Beyond Thresholds: A Quality-Aware Decision Intelligence Framework for Cold Chain IoT Systems

arXiv:2608.15082v1 Announce Type: new Abstract: Cold chain logistics has advanced technologically, yet most deployed systems remain reactive monitors, not decision-making agents: thresholds trigger al

Bye-bye, Bluebook? Automating Legal Drudgery With AI-Augmented Rule Following

arXiv:2505.02763v2 Announce Type: replace-cross Abstract: One of the central promises of legal AI is to automate drudgery -- the formal, repetitive tasks of lawyers' work that consume time without cal

LLMs for Zero-Shot Threat Detection via Structured Risk Indicators

model-releasesarxiv-cs-lg

arXiv:2608.16508v1 Announce Type: cross Abstract: We propose a two-stage large language model (LLM) framework for zero-shot detection of insider threats and advanced persistent threats (APTs) from het

Hardware

TERRA: A Hierarchical Parallel Training and Memory Orchestration Framework for High-Resolution AI-based Earth Modeling

arXiv:2608.15211v1 Announce Type: new Abstract: Training high-resolution AI-based Earth forecasting models is memory-intensive. Window-based Swin Transformers reduce the quadratic cost of global atten

hardwarearxiv-cs-cv

The Commercial Tax: Rent-vs-Own Blind Spots in Multi-Hop Retrieval Benchmarks

model-releasesarxiv-cs-cl

arXiv:2608.16096v1 Announce Type: cross Abstract: Enterprises connect language models to their own data through retrieval. The benchmarks that rank multi-hop retrieval systems leave out two facts a bu

The Hallucination Snowball: Modeling Error Propagation as State Transitions in Multi-Agent LLM Pipelines

arXiv:2608.14588v1 Announce Type: new Abstract: Sequential multi-agent LLM pipelines chain specialized agents without verification at handoffs, creating a structural flaw with measurable and severe co

A Calibrated Test of Internal Action Maps: State Signals Without Global Affine Closure

arXiv:2608.13626v1 Announce Type: new Abstract: A hidden state signal can be decodable or causally usable without supporting a reusable action map. We test whether action maps fitted without a source

AnchorBench: A Multi-Pathway Benchmark for the Anchoring Effect in LLMs

arXiv:2608.14320v1 Announce Type: new Abstract: The anchoring effect is a cognitive bias in which an initial reference value shifts a later judgment toward itself. This effect is well established in h

Applications

Building AI-Intensive Software with AI: Early Results and a Cautionary Tale on Measuring Development Cost

arXiv:2608.13730v1 Announce Type: cross Abstract: Empirical reports on the true cost of AI-intensive software development remain scarce, and the few that exist are easy to get wrong in ways that never

applicationsarxiv-cs-ai

MemoryLake on MemoryArena: A Matched Study of Agent Memory Backends

arXiv:2608.13883v1 Announce Type: new Abstract: Most agent-memory benchmarks test post-hoc recall, whereas MemoryArena evaluates whether memory supports interdependent, multi-session task completion.

Qwen 3.8 27B Overthinking, It has to be done, it has to be overthinking to punch Opus 4.6

Yes, it sucks to waste time waiting on 16K+ reasoning tokens alone. But here's the thing, this is only a 27B model trying to perform on par with 1T+ parameter models. Something has to be sacrificed, a

Repair, Not Improvement: Decomposing Constrained Decoding in Tool-Call Abstention

arXiv:2608.13959v1 Announce Type: new Abstract: Function calling is what the recent accounting of constrained generation explicitly sets aside: it finds the decoder's contribution small for format con

researcharxiv-cs-cl

AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models

arXiv:2608.13472v1 Announce Type: cross Abstract: Analog circuit design is a time-consuming, iterative process in a nonlinear and high-dimensional design space that relies heavily on expert intuition.

Built a Mac app that actually uses Ollama for work, not just chat — with a calibration step for models with flaky tool calling

Most Ollama frontends I've tried are chat UIs with tool calling bolted on as an afterthought, which is fine until you actually try to make a small local model do multi-step work and it silently emits

model-releasesr-ollama

CangjieBench: Benchmarking LLMs on a Low-Resource General-Purpose Programming Language

arXiv:2603.14501v2 Announce Type: replace-cross Abstract: Large Language Models excel in high-resource programming languages but struggle with low-resource ones. Existing research related to low-resou

Generative Universal Multimodal Retrieval with Dual-role Identifiers

arXiv:2608.12987v1 Announce Type: cross Abstract: Generative information retrieval (GIR) has emerged as a compelling alternative to the conventional index-retrieve-then-rank retrieval pipeline by trai

Local Ai

LLMs Are Not Good Strategists, Yet Memory-Enhanced Agency Boosts Reasoning

arXiv:2608.12626v1 Announce Type: cross Abstract: Strategic reasoning in Large Language Models (LLMs) within long-horizon environments is often limited by inconsistent subgoals. In these settings, fin

local-aiarxiv-cs-ai

Safety

Reconcile Once, Write Anytime: A Trust-Tiered Librarian and a Multi-Agent Writer for Drift-Free, Point-in-Time Research

arXiv:2608.12984v1 Announce Type: cross Abstract: Long-form research reports generated by large language models drift, contradict themselves, and lose provenance: the same metric appears with differen

safetyarxiv-cs-cl