Search: “persistence”

Ansari: A Retrieval-Grounded Islamic AI Assistant -- Architecture, Deployment, and Lessons from 140,000 Conversations

arXiv:2608.20390v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) are increasingly used to answer religious questions, but for Islamic content they carry two serious risks

safetyarxiv-cs-ai

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Applications

EviRank: Structured Relevance Evidence for Multimodal Image Re-ranking

DGX agent

arXiv:2608.20886v1 Announce Type: new Abstract: Real-world image search queries are multimodal and compositional: ``find this shirt in pink'' specifies an entity to retain, an attribute to modify, and

applicationsarxiv-cs-cv

24 Aug 2026

Generating Multi-view Adversarial Examples for Visual Geometry Grounded Transformer

arXiv:2608.20748v1 Announce Type: new Abstract: The Visual Geometry Grounded Transformer (VGGT) enables unified feed-forward 3D reconstruction from multi-view images. However, deploying such a high-pe

safetyarxiv-cs-cv

Applications

Perseus: Interactive Time Series Segmentation with Sparse Supervision via Stateful Memory

arXiv:2510.09930v2 Announce Type: replace-cross Abstract: Real-world systems, ranging from industrial manufacturing to wearable healthcare, generate multivariate time series with hierarchical states r

applicationsarxiv-cs-ai

Real local agentic coding on a 12GB VRAM budget.

Thanks to Unsloth Dynamic 3.0 quants coming in slightly leaner and better preserved, I settled on Qwen 3.8 27B (`UD_Q4_K_XL`) at 100K context as my daily driver for Hermes Agent and OpenCode. On an RT

Training, learning and inference: unified dynamics of neural systems

model-releasesarxiv-cs-lg

arXiv:2608.20965v1 Announce Type: new Abstract: We define an atomic generation fact f=(u,tau,omega,z;rho), recording the origin, realized transformation, concrete occurrence, generated result and rela

ConceptGuard: Benchmarking Context-Sensitive Unlearning in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.20338v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly require selective removal of harmful or sensitive knowledge, called unlearning, yet existing methods and bench

DeltaMomentum: A Key-Value based Anisotropic Momentum Update via Delta Rule

arXiv:2608.19491v1 Announce Type: cross Abstract: Most modern optimizers form their momentum as an exponential moving average (EMA) of past gradients, forgetting every direction at one fixed rate. How

researcharxiv-cs-cl

Agents

From Prediction to Self: Developmental Conditions for Agency in Minimal Neural Systems

arXiv:2606.05605v2 Announce Type: replace Abstract: How does a system that merely predicts the world come to distinguish its own causal influence from everything else? We trace this transition in a mi

agentsarxiv-cs-lg

Agents

The Third Restructuring of Software Form: From the Three-Tier Architecture to Storage, Models, and Agents

arXiv:2608.20201v1 Announce Type: new Abstract: Software form has undergone two paradigm shifts since its inception: Software 1.0, in which instructions determine behavior, and Software 2.0, in which

agentsarxiv-cs-ai

Applications

High-Flux Count-Free Single-Photon 3D Cameras

arXiv:2608.18306v1 Announce Type: new Abstract: Single-photon cameras based on single-photon avalanche diode (SPAD) technology are gaining popularity for 3D sensing, thanks to their extreme sensitivit

applicationsarxiv-cs-cv

Off-Manifold Collapse in Guided Protein Language Models

arXiv:2608.18597v1 Announce Type: new Abstract: Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative

TinySearch v0.6.1 - still a lightweight web research tool for local LLMs, now with bring-your-own-browser support

Hey everyone, Posted TinySearch here a few versions ago and got a bunch of useful feedback, so figured I'd post an update because the thing has changed quite a bit since then. Repo: [https://github.co

Hardware

Tuning the Stochastic Machine: A Systems Engineer's Operating Model for Human-AI Engineering

arXiv:2608.19125v1 Announce Type: new Abstract: When an expert corrects an LLM assistant's error, the correction usually dies with the session, and the error class returns. I argue this is an operatio

hardwarearxiv-cs-ai

Encoded but Not Actionable: Auditing the Decode-Generate-Steer Gap in Frozen LLMs for Geometric Constraints

arXiv:2608.17843v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance on structured reasoning tasks, but what they encode and whether it informs model beh

The concentration game: Bayesian updating, regret, and information

arXiv:2608.18061v1 Announce Type: new Abstract: We give a two-player zero-sum repeated game between a learner and nature whose value identity generates Bayesian updating and an exact accounting of exp

Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight

arXiv:2510.08713v3 Announce Type: replace Abstract: Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typical

agent-memoryzepknowledge-graph

Tools

Zep

Human

Zep offers a knowledge graph for persistent user memory and shared organisational context through MCP, according to Zep.

Building operational resilience with agentic AI in financial services

model-releasesgoogle-cloud-ai

For financial institutions, operational resilience has long been embedded in regulatory and supervisory expectations — to say nothing of the high expectations of consumers. With the implementation of

Functional anatomy of Pythia-Herwig differences with Kolmogorov-Arnold networks

arXiv:2608.15952v1 Announce Type: cross Abstract: Differences between high-energy event generators can arise at several stages of the collision simulation, from the hard scattering through parton show

Kozuchi Agent: A Language-Agnostic Open-Weight Agent for Software Repair

arXiv:2608.15579v1 Announce Type: cross Abstract: Industrial software-engineering teams increasingly need LLM agents that turn bug reports into correct patches, yet benchmark-scale operation adds long

LENS: In-Context Search via Latent Evidence Exploration over Dynamic Raw Documents

arXiv:2608.16185v1 Announce Type: cross Abstract: LLM agents increasingly answer questions over dynamic raw-document collections, where files may change before preprocessing, and relevant evidence (sp

local-aiarxiv-cs-ai

Local Gains and Fixed-Assignment Set Losses in Shared Set Decoders

arXiv:2608.14717v1 Announce Type: new Abstract: A query-relation deletion can improve the edited slot while reducing the utility of the prediction set that contains it. We study this tension in two re

researcharxiv-cs-cv

Local Qwen 3.8 27B vs GPT‑5.6 Terra vs Grok 4.6

I gave three AI models the same brief: build a premium Three.js fragrance launch site from the same Git baseline, independently and with no collaboration. Three very different results. Here’s the full

model-releasesr-ollama

RISE: Roadside Infrastructure Sequence Understanding across 3D Tracking and Structured Vision-Language Reasoning

arXiv:2608.16480v1 Announce Type: cross Abstract: We present RISE (Roadside Infrastructure Sequence Understanding and Evaluation), a framework spanning metric 3D tracking and structured vision-languag

APTER: Adaptive Post-Training with Expert-Grounded Rubrics

arXiv:2608.14212v1 Announce Type: new Abstract: As large language models enter professional domains, they must satisfy domain constraints, include critical evidence, and provide complete reasoning rat

EXL3 seems to be fading from the r/LocalLLaMa consciousness, and while I suspected it, I'm surprised at this point in time.

EXL3 is an alternative to llama.cpp. And while there is extensive tooling for llama.cpp, EXL3's primary deployment (TabbyAPI), has a OpenAI compatible API so it shouldn't matter. Why won't this tool m

Investigating individual writing style as a contributor to gender gaps in science and technology

arXiv:2204.13805v5 Announce Type: replace-cross Abstract: Gender gaps in how scientific work is evaluated are well documented, but their sources remain debated. We ask whether an overlooked factor---t

safetyarxiv-cs-cl

MACS: A Hybrid Multi-Agent Framework for Reliable Conversational E-Commerce Recommendation

arXiv:2608.14068v1 Announce Type: cross Abstract: Conversational recommendation for e-commerce is increasingly mediated by large language models (LLMs), yet many real-world deployments operate under a

llama.cpp Windows Manager

https://github.com/alekk89/llama-cpp-windows-manager It has been three months since I first shared my personal solution for running llama.cpp on Windows, and the project has evolved considerably since

15 Aug 2026

Tutorials

Continual Distillation Learning for Rehearsal-Free Class-Incremental Learning via Decoupled Prompting

arXiv:2407.13911v5 Announce Type: replace Abstract: Prompt-based continual learning has shown strong performance in rehearsal-free class-incremental learning by adapting learnable prompts while freezi

tutorialsarxiv-cs-cv

Dual-Flow Transformers: Decoupling the Primary Prefill Path from Additional Decode Computation

arXiv:2608.12385v1 Announce Type: new Abstract: As large language models serve more requests, cumulative inference cost is becoming increasingly important relative to one-time training cost. The two i

Exploring Oversmoothing with Householder Matrices

arXiv:2608.12514v1 Announce Type: new Abstract: Deep graph neural networks(GNNs) suffer from oversmoothing- a progressive collapse of node representation towards a low information subspace as network

From Visual Widgets to UI Code: Efficient Tool-Grounded Generation

model-releasesarxiv-cs-cv

arXiv:2608.12611v1 Announce Type: new Abstract: Existing screenshot-to-code systems face a trade-off between flexibility and controllability. Direct multimodal generation can hallucinate visible detai

Detecting Explanatory Insufficiency in Learned Representations: A Framework for Representational Vigilance

arXiv:2606.13172v3 Announce Type: replace Abstract: Learned representations are central to modern machine learning and are typically evaluated through predictive performance, robustness, uncertainty e

local-aiarxiv-cs-lg

13 Aug 2026

Massive Activations in Hybrid Linear Attention Large Language Models: Pre-Attention Spikes and Inter-Spike Plateaus

arXiv:2608.12149v1 Announce Type: new Abstract: We present the first systematic study of Massive activations (MAs) in layer-interleaved HLA LLMs and uncover two architecture-aligned morphologies: MAs

researcharxiv-cs-cl

13 Aug 2026

Applications

StateFlow: Building, Evolving, and Accessing 3D World States for Previsualization

arXiv:2608.12314v1 Announce Type: new Abstract: Previsualization is an intermediate layer between ideas and production in film, games, architecture, and urban design. It lets creators iteratively refi

applicationsarxiv-cs-cv

13 Aug 2026

Agents

A Gateway Architecture for Enterprise MCP Authentication: Unifying Heterogeneous Auth, Identity Delegation, and the User / Non-User Persona Problem

arXiv:2608.10760v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has become the de-facto interface for connecting LLM agents to enterprise tools, and adoption has been explosive: wit

agentsarxiv-cs-ai

Embodied Multimodal Grounding for Open-Vocabulary Mobile Manipulation via Semantic 3D Gaussian Splatting

arXiv:2608.10756v1 Announce Type: cross Abstract: Embodied mobile manipulation requires language, visual observations, three-dimensional scene structure, and action feasibility to be aligned before ex

local-aiarxiv-cs-cv

Hardware

EvoMem: Memory-Augmented Evolution for Code Optimization

arXiv:2608.10795v1 Announce Type: new Abstract: Successful mutation strategies in evolutionary code search may contain reusable knowledge that is useful beyond a single run, and in some cases may tran

hardwarearxiv-cs-ai

Self-Correcting Long-Horizon Search Agents via Tree-Structured Memory

arXiv:2608.10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments. However, providing complete

TAF-MED: Multi-Turn Safety Refusal Collapse in LLMs Under Declared Self-Treatment Intent

arXiv:2608.10258v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly provide conversational health information that may influence treatment decisions, yet existing benchmarks do

A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration

arXiv:2608.08689v1 Announce Type: new Abstract: The state evolution of a complex system arises jointly from object laws, relational propagation, domain conservation, and unmodeled error. Forcing all s

safetyarxiv-cs-ai

Continued development of the model based on the SSN [D]

researchr-machinelearning

Back after ~6 months — rebuilding my spiking language model around CPU-first inference Hey everyone. It’s been around six months since I last posted anything about this project here. Some of you might

EndoMD-SLAM: Endoscopic Gaussian Splatting SLAM under Optical Degradation with Memory and Static-Transient Decomposition

model-releasesarxiv-cs-cv

arXiv:2608.08949v1 Announce Type: new Abstract: Dense 3D reconstruction is critical for clinical endoscopic navigation and documentation. While Gaussian Splatting SLAM systems show promise in this dom

MiniMax-H3: ~38 GB less VRAM with Runtime LoRA Bypass — DoRA Dynamic LoRA Loader v1.0.39

local-air-stablediffusion

GitHub: https://github.com/xmarre/ComfyUI-DoRA-Dynamic-LoRA-Loader Release v1.0.39: https://github.com/xmarre/ComfyUI-DoRA-Dynamic-LoRA-Loader/releases/tag/v1.0.39 Also available through ComfyUI Manag

MOSAIC: Adversarial Co-evolution of Specialist Heuristics and Problem Instances for LLM-based Automated Heuristic Design

arXiv:2608.07544v1 Announce Type: cross Abstract: Automated heuristic design (AHD) with large language models (LLMs) has produced strong heuristics for combinatorial optimization problems (COPs). Yet

Online Learning of Scale Parameters in Score-Driven Filters

arXiv:2608.09218v1 Announce Type: new Abstract: Score-driven filters multiply a scaled log-likelihood score by a gain that controls the update magnitude. We treat this gain as a decision variable and