Search: “context”

From weeks to minutes: The new agentic era of data pipelines

model-releasesgoogle-cloud-ai

Data pipelines are the backbone of the modern enterprise, yet a barrier to entry exists for orchestrating them, making this critical capability unavailable to many data professionals. Following our an

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Local Ai

How bad do you think models like Qwen3.8-27B or GLM-5.3-Flash would be with H-Neurons disabled?

DGX agent

TL;DR: this paper proposes a method to fix hallucination rates to very low levels or zero by disabling neurons which contribute to hallucination. This discovery has been out for a while now, but it ha

local-air-localllama

31 Aug 2026

PRISM: Agentic Retrieval with LLMs for Multi-Hop Question Answering

arXiv:2510.14278v2 Announce Type: replace Abstract: Retrieval plays a central role in multi-hop question answering (QA), where answering complex questions requires gathering multiple pieces of evidenc

agentsarxiv-cs-cl

Safety

Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation

arXiv:2603.21366v2 Announce Type: replace Abstract: Autoregressive video diffusion has recently emerged as a promising paradigm for long-video generation, enabling causal synthesis beyond the temporal

safetyarxiv-cs-cv

Retrieving Relations, Detecting Fallacies: A RAG Approach to Political Debate Analysis

arXiv:2608.27471v1 Announce Type: cross Abstract: Fallacies are arguments that employ invalid reasoning, making their automatic detection critical in sensitive contexts such as high-stakes political d

Select, Don't Train: The Benefits of Modular Entity Disambiguation with LLM-Based Selection

arXiv:2608.27470v1 Announce Type: new Abstract: Entity Disambiguation (ED) is a key task for constructing and using knowledge graphs. State-of-the-art neural approaches commonly model ED as a single t

SignRR: Retrieve and Refine Real Motion for Sign Language Production

arXiv:2608.28568v1 Announce Type: new Abstract: Sign language production (SLP) aims to generate continuous signing motion from spoken language, often through gloss-to-pose generation. Prior work mainl

applicationsarxiv-cs-cv

Sledgehammer or Scalpel? A Fine-grained Adaptive Framework for Implicit Hate Speech

arXiv:2608.27462v1 Announce Type: new Abstract: Unlike explicit attacks with obvious profanity, implicit hate speech hides malice within seemingly compliant expressions through metaphors and contextua

Sliding-window beats linear attention

arXiv:2608.28444v1 Announce Type: new Abstract: Due to the nature of quadratic attention, Large Language Models (LLMs) consume a lot of memory and energy. Every new token costs more than the previous

researcharxiv-cs-cl

Var-JEPA: A Variational Formulation of the Joint-Embedding Predictive Architecture - Bridging Predictive and Generative Self-Supervised Learning

arXiv:2603.20111v2 Announce Type: replace Abstract: The Joint-Embedding Predictive Architecture (JEPA) is often seen as a non-generative alternative to likelihood-based self-supervised learning, empha

applicationsarxiv-cs-lg

b10690

model-releasesllama-cpp-releases

memory : copy Hadamard matrix to k_rot tensor only if it has buffer assigned to prevent crashes during context shift of unquantized K cache (#27967) Co-authored-by: Stanisław Szymczyk sszymczy@gmail.c

I collected every single LLM coding benchmark, and computed their Intelligence Density

The intelligence in my context is an aggregate index, I called the Agentic Coding Index, across most relevant agentic coding benchmarks: SWE-bench Pro, DeepSWE v1.1, Terminal-Bench (v4, v3, v2.1), Cod

Qwen3.8-Flash-Next optimised for Macs

Running on a M1 Max 64 GB: - SSD streaming for tensors - SSD streaming for engrams - SSD streaming for MTP How is it possible? * Custom Q4 quant: benchmarked all metal tensors then picked and spliced

Local Ai

Qwen3.8-Flash-Next turns 4xR9700 into a local AI powerhouse! 120 t/s TG and 12k t/s PP single request with optimized vLLM

If you own 4xR9700 and were waiting for the model to make them shine, then I have some good news for you! It's running at 80-120 tokens/second for generation and 12k token/second prefill for a single

local-air-localllama

// Memory is what breaks long-horizon agents // It's undeniable how important memory/recall is for long-horizon tasks. If you are building f…

// Memory is what breaks long-horizon agents // It's undeniable how important memory/recall is for long-horizon tasks. If you are building for long-horizon tasks, this is a great read. (bookmark it) T

model-releasesdair-ai--x

29 Aug 2026

A Multi-Framework Comparison of Outline Stages in Long-Form Generation with LLMs

arXiv:2608.26177v1 Announce Type: cross Abstract: Long-form generation exposes fundamental limitations of large language models. Even 70B-parameter models exhibit length collapse at 16k-token outputs,

AffectOmni: RL-Verifiable People-Centric Grounded Affective Reasoning for Social and Art-Related Scenes

arXiv:2608.26193v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) achieve strong performance on VQA and scene understanding, yet affective reasoning remains vulnerable to shortc

researcharxiv-cs-ai

Dependency-Aware Revocable Decoding for Efficient Diffusion Large Language Model Inference

arXiv:2608.26574v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer a promising alternative to autoregressive generation by decoding multiple tokens in parallel through itera

researcharxiv-cs-cl

Finding the Right Evidence: Factor-Guided Coarse-to-Fine Reasoning for Long Videos

arXiv:2608.26355v1 Announce Type: new Abstract: While LVLMs rapidly improve, long-video question answering still remains challenging: relevant evidence is sparse, and question-relevant context often f

agentsarxiv-cs-cv

GraphMemix: Query-Aware Evidence Forests for Long-Term Multimodal Agent Memory

arXiv:2608.26983v1 Announce Type: new Abstract: Organizing long-term memory for multimodal agents remains challenging because existing methods either suffer from expensive question-agnostic offline su

Invocation-Level Reliability of Tool-Using Agents

arXiv:2608.26189v1 Announce Type: new Abstract: Tool-using agents fail two ways: choosing the wrong tool, or forming wrong arguments, and an early failure of either kind can silently corrupt everythin

Knowing When Not to Reuse: Conditional Experience Transfer in Autonomous LLM Post-Training

arXiv:2608.26730v1 Announce Type: new Abstract: Large language models offer broad capabilities, but adapting them to evolving domains, tools, and requirements often entails repeated post-training. Aut

Ring Forcing: Towards Precise Long-Term Memory for Autoregressive Video Diffusion

arXiv:2608.26794v1 Announce Type: new Abstract: Scaling video generation to long durations reveals a critical bottleneck: current models lack robust long-term memory. This deficiency can be studied al

researcharxiv-cs-cv

Scaling Graph Neural Networks for Friend Recommendation: Multi-Hash User Embeddings and Temporal Neighbor Sampling

arXiv:2608.27413v1 Announce Type: cross Abstract: Friend recommendation is inherently graph-structured: the relevance of a potential connection depends on multi-hop social context rather than user att

applicationsarxiv-cs-lg

Tests de maîtrise du français : les modèles chinois (DeepSeek, GLM, Kimi) face à une grille critériée

Post rédigé avec l'aide de GLM5.3 flash Contexte : formateur professionnel d'adultes en France, j'utilise des agents LLM au quotidien et le français qu'ils produisent est mon critère n°1, avant les be

model-releasesr-ollama

The Thousand-Graph Hypothesis: A Testable Hypothesis of Task-Conditioned Relation Materialization in Repository-Level Code Reasoning

arXiv:2608.26602v1 Announce Type: cross Abstract: Large software repositories are often beyond model context limits. Training repository knowledge into models is costly and quickly stale, while local

DESCENT: Directed Edge Scene Encoding for Airport Surface Movement Prediction

model-releasesarxiv-cs-ro

arXiv:2608.26002v1 Announce Type: new Abstract: Advanced automation is a key technology for enhancing the safety of ground operations amidst the increasing density of commercial air traffic. While mot

Layer-Order Inversion: Rethinking Latent Multi-Hop Reasoning in Large Language Models

arXiv:2601.03542v2 Announce Type: replace Abstract: Large language models (LLMs) perform well on multi-hop reasoning, yet how they internally compose multiple facts remains unclear. Recent work propos

applicationsarxiv-cs-cl

Mind2Report: Expert-Level Commercial Report Synthesis via Cognitive Deep Research Agent

arXiv:2601.04879v2 Announce Type: replace Abstract: Synthesizing informative commercial reports from massive and noisy web sources is critical for high-stakes business decisions. Although recent deep

PonsRAG: A Pons-Inspired RAG Bridging Cognitive Islands for Coordinated Long Narrative Reasoning

arXiv:2608.25486v1 Announce Type: cross Abstract: Long Narrative Reasoning is an essential capability for processing and reasoning over complex narratives. While retrieval-augmented generation provide

researcharxiv-cs-cl

Qwen3.8-Flash on @qwen_cloud: 0.15/1M input tokens, 0.47/1M output tokens, and just $0.016/1M on cache hits. ☁️ Come give it a try! 👇

Qwen3.8-Flash on @qwen_cloud: 0.15/1M input tokens, 0.47/1M output tokens, and just 0.016/1M on cache hits. ☁️ Come give it a try! 👇 Qwen3.8-Flash API is live on QwenCloud. 262K native context, extens

model-releasesqwen--x

Running local LLM's as agents in Claude Code

I hit my token limit three times a day on my max subscription - got sick of that and designed this MCP setup to shift some of the coding load to my local Qwen3.8-27B model. I've been iterating on it n

SeVeR: Selective Visual Exposure and Retrieval for 3D Medical Image Question Answering

model-releasesarxiv-cs-cv

arXiv:2608.25630v1 Announce Type: new Abstract: Volumetric medical VQA requires reasoning over long and redundant 3D visual token sequences, especially in multi-sequence MRI where complementary modali

What are the most frustrating silent failures you've encountered with local LLMs?

I've been building a small tool opensource project that sits between applications and local LLM servers (starting with Ollama) to diagnose silent inference failures instead of just showing logs. Thing

model-releasesr-ollama

Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)

arXiv:2608.23858v1 Announce Type: cross Abstract: The Agent Payments Protocol (AP2), introduced by Google, enables large language model (LLM)-driven shopping agents to authorize and execute payments o

Design-to-Plan: A Large Language Model-Based Multi-Agent Framework for Manufacturing Process Planning from 3D CAD Models and 2D Engineering Drawings

arXiv:2608.24039v1 Announce Type: cross Abstract: Manufacturing process planning transforms heterogeneous design information into coherent manufacturing decisions. However, existing approaches focus o

Feedback That Backfires: Why Small Language Model Agents Repeat the Call They Just Watched Fail

arXiv:2608.23651v1 Announce Type: cross Abstract: Agent harnesses record a failed tool call and its error message in the transcript and ask the model to continue, on the assumption that the error is c

First serious confirmation. Ox Alpha is GLM-5.3-Flash

https://x.com/romanchernin/status/2092488160680751437?s=20 - Multimodal (Vision) - 1M Tokens Context Window - DeepSWE ~63% EDIT: THE ORIGINAL POST IS GONE Roman Chernin @romanchernin The mysterious Ox

MolEmb: Multimodal Large Language Models Can Be Strong Molecular Embedding Models

arXiv:2608.23646v1 Announce Type: new Abstract: Molecular embedding models can serve as foundational infrastructure for computational chemistry and drug discovery, where reusable vector representation

SyPS: Measuring Sycophancy Prompt Sensitivity in Large Language Models

arXiv:2608.23837v1 Announce Type: new Abstract: Large language models (LLMs) are known to exhibit social sycophancy, often validating or agreeing with users in socially sensitive contexts. Existing ev

researcharxiv-cs-ai

TrustShiftProbe: Characterizing, Benchmarking, and Defending Staged Trust Attacks on MCP Servers

arXiv:2608.23763v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has emerged as the standard layer connecting Large Language Model agents to external tool backends. This openness int

we made Qwen 3.8 27b MLX vision quants and compared them against other popular community publishers (lm-studio, lukaskremla, mlx-community and etc)

we made vision mlx quants of qwen3.8 27b (9 builds from 8bit at 29.5 GB down to 3.23bpw DWQ at 11.8 GB) and compared them against other community vision mlx quants from hf (we only compared vision bui

Act with Intent: Distilling Behavior Intent for Vision-Language-Action Models

arXiv:2608.23478v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models can turn multimodal context into robot actions, but their action decoders are still trained largely by behavior cl

applicationsarxiv-cs-ai

Clarify User Expertise: Towards Proactive Conversational Agents Tailoring Responses to User Proficiency

arXiv:2608.22266v1 Announce Type: new Abstract: In the context of information seeking, conversational agents are undergoing an evolution from reactive tools to proactive, personalized assistants. A cr

Local Ai

For those of us running Ollama on whatever hardware we already have: r/LowEndLocalAI

One of the things I like most about Ollama is how low it makes the barrier to experimenting with local models. The downside is that once you move away from high-end hardware, finding the right informa

local-air-ollama

From SQL Generation to Tool Selection: A Domain-Oriented Pattern for MCP Servers

arXiv:2608.22063v1 Announce Type: new Abstract: Agents built on Large Language Models (LLMs) increasingly reach enterprise data through the Model Context Protocol (MCP), and many MCP database servers

ibm-granite/granite-4.2-30b · Hugging Face

Granite-4.2-30B is the flagship reasoning model in the Granite 4.2 family. It delivers the strongest performance across reasoning-intensive tasks by leveraging built-in <think>...</think> chain-of-tho

M5 Ultra 96GB vs M5 Max 128GB — is 2x bandwidth worth losing 32GB of RAM, with Qwen3.8-Flash-Next dropping tomorrow?

I’ve been going back and forth on this for a week and I can’t settle it, so I’m hoping someone here has hands-on numbers. The two configs (German prices, dealer quote, incl. VAT): Config Price Mac Stu