Search: “llm”

The agent-first cloud: why we built Managed Agents

model-releasesdigitalocean

Compute (EC2) opened the front door to the first generation cloud. Agents need something different: compute, inference, and data working as one. We built the cloud that delivers all three as one simpl

25 Sept 2026

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

When Should Forecasting Agents Reason? Behavioral Stress Tests for Reliability Routing

DGX agent

arXiv:2609.28475v1 Announce Type: new Abstract: Forecasting agents increasingly combine language-model reasoning, retrieval, ensembling, and calibration, but it remains unclear when each behavior shou

agentsarxiv-cs-ai

25 Sept 2026

Applications

A Resilience Recovery Method for Complex Traffic Network Security Based on Trend Forecasting

arXiv:2609.27903v1 Announce Type: new Abstract: Due to the rapid development of information technology, a huge and complex traffic network has been established across various sectors, including aviati

applicationsarxiv-cs-ai

'AI Is Turning Too Human': How Teenagers Experience and Negotiate AI in Everyday Life

arXiv:2609.27824v1 Announce Type: new Abstract: Generative AI is rapidly entering adolescents' everyday lives during a critical period of cognitive, social and emotional development. Yet its adoption

safetyarxiv-cs-cl

Alignment Inertia: Auditing the Durability of Training Data Influence Through Policy Override Resistance

arXiv:2609.27333v1 Announce Type: new Abstract: Platform operators increasingly rely on system prompts and fine-tuning to govern model behavior, yet it remains unclear how reliably these interventions

An Open Pipeline and Dashboard for Systemic-Risk Evidence under the EU AI Act's Code of Practice

arXiv:2609.28335v1 Announce Type: new Abstract: Claims about AI safety reach audiences well beyond the AI community, yet many rely on opaque evidence or static assessments, when supporting evidence is

ASCIIBench: Evaluating Language-Model-Based Understanding of Visually-Oriented Text

model-releasesarxiv-cs-lg

arXiv:2512.04125v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated several emergent behaviors with scale, including reasoning and fluency in long-form text generation.

Automated Extraction of Records of Processing Activities (RoPA) Using Hybrid RAG and Locally Deployed Large Language Models

arXiv:2609.27359v1 Announce Type: new Abstract: Vietnam's Personal Data Protection Law (Law No. 91/2025/QH15) and Decree No. 356/2025/ND-CP, effective January 1, 2026, require organizations to establi

btw i had no idea what i was doing when i started this but learned so much about models in the process and feel like i have a much better se…

btw i had no idea what i was doing when i started this but learned so much about models in the process and feel like i have a much better sense of what’s happening under the hood managing someone (an

agentsyohei-nakajima--x

CART: Closed-Loop Adaptive Red Teaming for Large Language Models

arXiv:2609.27336v1 Announce Type: new Abstract: Automated red teaming often replays a fixed set of prompts, which measures known risks but cannot learn from failures found during testing. We present C

Controlling Collectives of AI Agents in Reasoning Space with Spatial Transformers

arXiv:2609.28247v1 Announce Type: cross Abstract: Large Language Models (LLMs) introduce an exciting new paradigm for planning and navigation in robotics, but fail on even simple multi-robot tasks as

local-aiarxiv-cs-ai

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms

arXiv:2609.28430v1 Announce Type: new Abstract: This work addresses continuous depression-severity score prediction from clinical interview transcripts under data scarcity. We propose a sequential low

Deploy and manage coding agents at scale with the Unity Gateway CLI

The article introduces the Unity Gateway Command Line Interface (CLI) as a tool for deploying and managing coding agents at large scale. It outlines how users can automate agent deployment, monitor pe

model-releasesdatabricks

EduBehaviors: Assertion-based Schemas for Auditable Coding of Educational Dialogues

arXiv:2609.27043v1 Announce Type: new Abstract: Large language models have allowed the rapid deployment of pedagogical annotations corresponding to constructs of interest, allowing a natural language

EidosDoc: Implicit Structure Encoding for Cost-Effective Semi-Structured Document QA

arXiv:2609.27784v1 Announce Type: cross Abstract: Semi-structured documents are ubiquitous in scientific reports, financial statements, and technical manuals. Question answering over such documents re

EMA: Elastic and Performance Transparent Memory Across GPUs

arXiv:2609.27040v1 Announce Type: cross Abstract: Multi-GPU servers have become the standard building block of modern data centers, providing aggregated capacity through high-bandwidth interconnects.

local-aiarxiv-cs-ai

EnComp: Lightweight Encoder-Only Context Compression for Retrieval-Augmented Question Answering

arXiv:2603.09222v2 Announce Type: replace Abstract: Efficient context compression is critical for retrieval-augmented question answering in resource-constrained settings, where long retrieved contexts

FLEET: From Logits Entropy to Enhanced Trajectories in Text Generation

arXiv:2609.27657v1 Announce Type: cross Abstract: Solutions based on large language models (LLMs) often rely on temperature sampling to improve accuracy and stability by aggregating multiple samples f

From Sentiment Classification to Actionable and Responsible Feedback: A Scoping Review and Evidence Map of NLP in Student Evaluation of Teaching, 2015-2026

arXiv:2609.27939v1 Announce Type: new Abstract: Natural language processing (NLP) applied to open-ended teaching-evaluation comments (Student Evaluation of Teaching, SET) has tracked the field's techn

safetyarxiv-cs-cl

Giving Credit Where It's Due: Redundancy-Aware Learning for Efficient Reasoning

arXiv:2609.27156v1 Announce Type: new Abstract: Large reasoning models can produce correct yet unnecessarily long reasoning traces. Existing methods improve reasoning efficiency with trajectory-level

local-aiarxiv-cs-cl

Hidden not Deleted: How Networks Suppress Entangled Features

arXiv:2609.27593v1 Announce Type: cross Abstract: Concept erasure methods that operate via linear projection assume that features occupy separable subspaces. We show this assumption fails under dense

Hunyuan-A13B Technical Report

arXiv:2609.27284v1 Announce Type: new Abstract: We present Hunyuan-A13B, an open-source large language model based on a Mixture-of-Experts architecture. It contains 80 billion total parameters but act

I built an air-gapped, local-first synthetic data generator powered by Ollama

Hey everyone, A major issue when building test environments or fine-tuning pipelines is balancing data realism with privacy. Pasting real internal/client data into cloud endpoints is a massive complia

local-air-ollama

I built an open-weight alternative to Jev / TypeSafe - introducing OpenJudgement-4B (early preview)

model-releasesr-localllama

I’m releasing OpenJudgement-4B-Preview, an experimental Qwen-based model fine-tuned on custom datasets for classification, scoring and true/false judgments. It scores answer options directly, and Pyth

Tutorials

Meet, Compare, or Abstain: LatWeave for Deterministic Multi-Hop Question Answering on Knowledge Lattices

arXiv:2609.27225v1 Announce Type: cross Abstract: Probabilistic question-answering systems -- whether large language models (LLMs) themselves, retrieval-augmented generation (RAG), or trained multi-ho

tutorialsarxiv-cs-ai

Tutorials

Pay attention to this new wave of System One models if you are building custom harnesses. First Jev. Now, Contrastive Language Model (CLM). …

Pay attention to this new wave of System One models if you are building custom harnesses. First Jev. Now, Contrastive Language Model (CLM). CLM is 9x faster than Jev. CLM seems to be a better verifier

tutorialsdair-ai--x

Quantifying the Occult: A Comparative Study of Hindu and Buddhist Deities Using Machine Learning Methods

model-releasesarxiv-cs-lg

arXiv:2609.27074v1 Announce Type: cross Abstract: This study introduces a dual-matrix computational architecture to mathematically quantify the morphological and theological divergence of 196 Hindu an

SafeTutors: Benchmarking Pedagogical Safety in AI Tutoring Systems

arXiv:2603.17373v2 Announce Type: replace Abstract: Large language models are rapidly being deployed as AI tutors, yet current evaluation paradigms assess problem-solving accuracy and generic safety i

Shopping by algorithm: How agentic AI deploys human heuristics as a surrogate consumer

arXiv:2609.28372v1 Announce Type: cross Abstract: Consumers increasingly delegate purchasing decisions to Large Language Models (LLMs) acting as surrogate consumers. Using 'Tool-Lab,' an adaptation of

StudentBench: AI and human tutoring yield equivalent GRE learning gains

arXiv:2609.28470v1 Announce Type: new Abstract: Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advanci

Today we establish that AI is as good as expert human tutors for immediate GRE learning gains (p=.015, n=2,383 students, study conducted Jul…

model-releasesjeremy-howard--x

Today we establish that AI is as good as expert human tutors for immediate GRE learning gains (p=.015, n=2,383 students, study conducted July-Sep 2026). One hour with an expert GRE tutor: $75. One equ

A guide to speeding up your video processing with AlphaEvolve

model-releasesgoogle-cloud-ai

In real-time streaming, every millisecond counts. For example, at 30 frames per second (fps), developers have a strict frame budget of just 33.3 ms (and only 16.6 ms at 60 fps) to ingest camera frames

BananaVLM: A Domain-Adapted Vision Language Model for Banana Crop Disease Diagnosis

model-releasesarxiv-cs-cv

arXiv:2609.25040v1 Announce Type: cross Abstract: Banana crop diseases threaten food security across the world, yet field diagnosis remains difficult because of limited expert access and visual simila

CoEvo: Oracle-Grounded Self-Evolution of a Single Model for Multi-Step Causal Reasoning

arXiv:2609.26094v1 Announce Type: new Abstract: Multi-step causal reasoning requires chaining inferences where each step constrains the next. An early error propagates silently, and a correct answer r

safetyarxiv-cs-lg

Conduct Under Pressure: What Sixty Language Models Do When a User Pushes

arXiv:2609.25447v1 Announce Type: new Abstract: We study what LLMs do when a user applies pressure in an uncomfortable situation: a user insists, begs, flatters or grieves, and the model gives up a co

CraftBench-UE: Deterministic Evaluation for Coding Agents in Unreal Engine

arXiv:2609.23142v1 Announce Type: new Abstract: Building gameplay features in a game engine requires more than code, as code that compiles and runs does not necessarily implement the requested gamepla

Decoding Guardrails: XAI-Guided Perturbation Analysis of Prompt Injection Detection

arXiv:2609.24801v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in production systems, raising concerns about their exposure to adversarial manipulation throug

safetyarxiv-cs-ai

Differentiable Fuzzy Inference Layer: A Monotone, Compositional Ordinal Reasoning Head for Large Language Models

arXiv:2609.26113v1 Announce Type: new Abstract: A state-of-the-art language model asked to interpret 'most of most students passed' typically answers 'most,' though composing two instances of 'most' y

Discovery-Driven Integration of Disjoint Tables via Text

arXiv:2609.26658v1 Announce Type: cross Abstract: Integrating heterogeneous datasets within data lakes is a critical challenge, particularly for semantically related tables that lack the explicit attr

local-aiarxiv-cs-cl

Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves

arXiv:2605.11280v2 Announce Type: replace-cross Abstract: Fast surrogate models for expensive simulations are now essential across the sciences, yet they typically operate as black boxes. We present e

Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning

arXiv:2505.13994v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy tra

Do Synthetic Personas Predict Real Audience Response? A Sim-to-Real Study Where a No-Persona Baseline Beats Persona-Based Copy Simulation

arXiv:2609.25010v1 Announce Type: cross Abstract: Marketers increasingly use large language models (LLMs) as 'synthetic personas' to predict how an audience will react to a piece of copy before it shi

DTOC: Dynamic Tool Output Compression for Adaptive Context Management in AI Agents

arXiv:2609.26121v1 Announce Type: cross Abstract: As agent capabilities have grown, practical limitations increasingly stem from constrained context windows rather than model capacity. Common strategi

Engram gone wild! 2b model update...

model-releasesr-localllama

Update from : https://old.reddit.com/r/LocalLLaMA/comments/1wis23s/update_small_model_engram/ It's been about a week so I'm back. People were asking me about the model. People wanted code, or models,

From Bits to Beliefs: Recoverable Semantic Fingerprints for Black-Box Verification of Large Language Models

arXiv:2609.24084v1 Announce Type: cross Abstract: Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification dif

Tutorials

Identifying Intelligent Processes via Online Sequential Testing

arXiv:2609.26193v1 Announce Type: cross Abstract: Active sequential hypothesis testing studies how to identify an unknown hypothesis with a given set of sensing actions. We study this in the setting o

tutorialsarxiv-cs-lg

Incremental Consistency Execution for Autonomous Intelligent Systems

arXiv:2609.24090v1 Announce Type: new Abstract: Long-horizon autonomous intelligent systems rely on heterogeneous components such as large language models, databases, external APIs, and rule engines,

safetyarxiv-cs-ai

LIMIT: Less Is More for Instruction Tuning in Text-to-SQL

arXiv:2609.24186v1 Announce Type: new Abstract: Large language models have achieved remarkable progress on Text-to-SQL through reasoning-enhanced fine-tuning, yet existing approaches predominantly rel