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Today, we’re announcing three new capabilities available in SageMaker Python SDK v3.8.0. In this post, we walk through each capability with code examples you can use to get started. For complete end-t

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Research

Accelerating AI-Powered Research: The PuppyChatter Framework for Usable and Flexible Tooling

DGX agent

arXiv:2605.17809v1 Announce Type: new Abstract: This research addresses the challenges inherent in developing Artificial Intelligence (AI) applications, particularly those leveraging Large Language Mo

researcharxiv-cs-ai

19 May 2026

Accelerating Inference for Multilayer Neural Networks with Quantum Computers

arXiv:2510.07195v2 Announce Type: replace-cross Abstract: Fault-tolerant Quantum Processing Units (QPUs) promise to deliver exponential speed-ups in select computational tasks, yet their integration i

Accelerating Rectified Flow Models via Trajectory-Aware Caching

arXiv:2605.16789v1 Announce Type: new Abstract: Diffusion and rectified flow (RF) models generate high-fidelity images and videos, but their iterative velocity-field evaluations are computationally ex

Accelerating Redshift-Conditioned Galaxy Image Synthesis with One-step Generative Modeling

arXiv:2605.17546v1 Announce Type: cross Abstract: Understanding galaxy morphology evolution across cosmic time requires models that can generate realistic galaxy populations conditioned on redshift. I

ACE: Self-Evolving LLM Coding Framework via Adversarial Unit Test Generation and Preference Optimization

arXiv:2605.16299v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at code generation but remain heavily reliant on large-scale annotated solutions and verification-based supervision

researcharxiv-cs-ai

Achieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization

arXiv:2310.07983v5 Announce Type: replace Abstract: The ProxSkip algorithm for distributed optimization is gaining increasing attention due to its effectiveness in reducing communication. However, exi

ACIL: Auto Chain of Thoughts for In-Context Learning

arXiv:2605.17088v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have shown that Chain-of-Thought (CoT) reasoning can substantially improve performance on complex reason

researcharxiv-cs-cl

Action-Gradient Monte Carlo Tree Search for Non-Parametric Continuous (PO)MDPs

arXiv:2503.12181v4 Announce Type: replace Abstract: Online planning in continuous state, action, and observation spaces remains challenging for autonomous systems. While Monte Carlo Tree Search (MCTS)

Actionable World Representation

arXiv:2605.18743v1 Announce Type: new Abstract: Inspired by the emergent behaviors in large language models that generalized human intelligence, the research community is pursuing similar emergent cap

safetyarxiv-cs-ai

Activation Steering with a Feedback Controller

arXiv:2510.04309v3 Announce Type: replace Abstract: Controlling the behaviors of large language models (LLM) is fundamental to their safety alignment and reliable deployment. However, existing steerin

Applications

Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning

arXiv:2605.17234v1 Announce Type: new Abstract: Predicting model performance at larger scales enables the design of training strategies and architectures tailored to specific performance targets. Empi

applicationsarxiv-cs-lg

Active Defense Against False Data Injection Attacks in Robotic Manipulators

arXiv:2605.17950v1 Announce Type: new Abstract: Robotic systems are vulnerable to False Data Injection Attacks (FDIAs), where adversaries corrupt sensor signals to gain malicious control. Feedback lin

researcharxiv-cs-ro

Active learning for photonic crystals

arXiv:2601.16287v3 Announce Type: replace-cross Abstract: Active learning for photonic crystals explores the integration of analytic approximate Bayesian last layer neural networks (LL-BNNs) with unce

Tutorials

AdaGraph: A Graph-Native Clustering Algorithm That Overcomes the Curse of Dimensionality and Enables Scientific Discovery

arXiv:2605.16320v1 Announce Type: cross Abstract: We present AdaGraph, a graph-native clustering algorithm born from the Structure-Centric Machine Learning (SC-ML) paradigm -- a new field of unsupervi

tutorialsarxiv-cs-ai

Adaptive Camera Sensor for Vision Models

arXiv:2503.02170v2 Announce Type: replace-cross Abstract: Domain shift remains a persistent challenge in deep-learning-based computer vision, often requiring extensive model modifications or large lab

Adaptive Control in Autonomous Driving via Real-Time Recurrent RL

arXiv:2602.02236v4 Announce Type: replace-cross Abstract: We study online fine-tuning of pretrained control policies for autonomous driving using Real-Time Recurrent Reinforcement Learning (RTRRL), a

Adaptive double-phase Rudin--Osher--Fatemi denoising model

arXiv:2510.04382v2 Announce Type: replace-cross Abstract: Even though more than 30 years have passed since the seminal Rudin--Osher--Fatemi (ROF) paper on total variation (TV) denoising, it remains re

researcharxiv-cs-cv

Adaptive Experimentation for Censored Survival Outcomes

arXiv:2605.18459v1 Announce Type: new Abstract: Adaptive experimentation enables efficient estimation of causal effects, but existing methods are not designed for survival data with censoring, where e

Adaptive Fused Prior Transfer for Controllable Generative Image Compression

arXiv:2605.16817v1 Announce Type: cross Abstract: Learned image compression has achieved competitive rate-distortion performance, but very-low-bitrate reconstruction remains difficult because the tran

Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification

arXiv:2605.17609v1 Announce Type: new Abstract: Many inference-time language-model pipelines combine a cheap reward signal with an expensive verifier, such as exact answer checking in mathematical rea

Local Ai

AdaptiveLoad: Towards Efficient Video Diffusion Transformer Training

arXiv:2605.17923v1 Announce Type: cross Abstract: In video generation models, particularly world models, training large-scale video diffusion Transformers (such as DiT and MMDiT) poses significant com

local-aiarxiv-cs-ai

Local Ai

ADMEDTAGGER: an annotation framework for distillation of expert knowledge for the Polish medical language

arXiv:2601.09722v2 Announce Type: replace-cross Abstract: In this work, we present an annotation framework that demonstrates how a multilingual LLM pretrained on a large corpus can be used as a teache

local-aiarxiv-cs-ai

ADR: An Agentic Detection System for Enterprise Agentic AI Security

arXiv:2605.17380v1 Announce Type: new Abstract: We present the Agentic AI Detection and Response (ADR) system, the first large-scale, production-proven enterprise framework for securing AI agents oper

Advancing content provenance for a safer, more transparent AI ecosystem

OpenAI discusses methods for establishing content provenance—tracking the origin and history of digital content—to improve transparency and safety in AI systems. The work addresses how verifiable cont

model-releasesopenai

Advancing Narrative Long Video Generation via Training-Free Identity-Aware Memory

arXiv:2605.18733v1 Announce Type: new Abstract: Autoregressive video generation has improved rapidly in visual fidelity and interactivity, but it still suffers from long-term inconsistency and memory

Adversarial Agent Collaboration for Correctness Improvements of C to Safe Rust Translation

arXiv:2510.03879v3 Announce Type: replace-cross Abstract: Translating C to memory-safe languages, like Rust, prevents critical memory safety vulnerabilities that are prevalent in legacy C software. Ev

Adversarial Attacks on Downstream Weather Forecasting Models: Application to Tropical Cyclone Trajectory Prediction

arXiv:2510.10140v2 Announce Type: replace Abstract: Deep learning-based weather forecasting (DLWF) models leverage past weather observations to generate future forecasts, supporting a wide range of do

Adversarial Fragility and Language Vulnerability in Clinical AI: A Systematic Audit of Diagnostic Collapse Under Imperceptible Perturbations and Cross-Lingual Drift in Low-Resource Healthcare Settings

arXiv:2605.16993v1 Announce Type: cross Abstract: Current clinical artificial intelligence (AI) systems are evaluated almost exclusively on clean, standardised, English-language inputs, conditions tha

safetyarxiv-cs-ai

AffordVLA: Injecting Affordance Representations into Vision-Language-Action Models via Implicit Feature Alignment

arXiv:2605.17517v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models have shown strong potential for general-purpose robotic manipulation. However, the visual represe

safetyarxiv-cs-ro

Agent Bazaar: Enabling Economic Alignment in Multi-Agent Marketplaces

arXiv:2605.17698v1 Announce Type: new Abstract: The deployment of Large Language Models (LLMs) as autonomous economic agents introduces systemic risks that extend beyond individual capability failures

AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent

arXiv:2602.03955v2 Announce Type: replace Abstract: While large language model (LLM) multi-agent systems achieve superior reasoning performance through iterative debate, practical deployment is limite

Agentic AI Governance and Lifecycle Management in Healthcare

arXiv:2601.15630v2 Announce Type: replace Abstract: Healthcare organizations are beginning to embed agentic AI into routine workflows, including clinical documentation support and early-warning monito

Agentic AI Translate: An Agentic Translator Prototype for Translation as Communication Design

arXiv:2605.17041v1 Announce Type: cross Abstract: We present Agentic AI Translate, an agentic translator prototype that operationalises the thesis of Yamada (forthcoming) -- that the metalanguage of T

Agentic Chunking and Bayesian De-chunking of AI Generated Fuzzy Cognitive Maps: A Model of the Thucydides Trap

arXiv:2605.17903v1 Announce Type: new Abstract: We automatically generate feedback causal fuzzy cognitive maps (FCMs) from text by teaching large-language-model agents to break the text into overlappi

Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics

arXiv:2605.17831v1 Announce Type: new Abstract: Query optimization in big data analytics remains computationally expensive, particularly for resource-constrained environments where traditional optimiz

agentsarxiv-cs-lg

Agentic Pipeline for Self-Synchronized Multiview Joint Angle Monitoring in Uncalibrated Environments

arXiv:2605.16419v1 Announce Type: cross Abstract: Kinematic monitoring plays a critical role in long-term rehabilitation for patients with spinal cord injury (SCI), where multi-view markerless motion

Agentic success has a prerequisite — building the systems most enterprises left undone

Enterprises racing toward assured autonomy in agentic AI are running headlong into a decades-old problem: Most of their infrastructure was never designed to be connected — let alone governed at the sp

agentssiliconangle

AgentKernelArena: Generalization-Aware Benchmarking of GPU Kernel Optimization Agents

arXiv:2605.16819v1 Announce Type: cross Abstract: GPU kernel optimization is increasingly critical for efficient deep learning systems, but writing high-performance kernels still requires substantial

Local Ai

Agentmw: Open-source middleware for AI agents — catches mid-run failures,compresses stale context, and grows a reasoning library across runs. Any model, any framework.

Agentmw is an open-source middleware framework designed to enhance AI agent reliability and efficiency across different models and frameworks. It addresses key operational challenges including mid-run

local-air-ollama

Agents for Experiments, Experiments for Agents: A Design Grammar for AI-Enabled Experimental Science

arXiv:2605.17746v1 Announce Type: new Abstract: AI systems are becoming active participants in organizational and knowledge work. They increasingly interact with humans, coordinate workflows, and oper

AgentSteerTTS: A Multi-Agent Closed-Loop Framework for Composite-Instruction Text-to-Speech

arXiv:2605.17583v1 Announce Type: new Abstract: While existing text-to-speech (TTS) models exhibit high expressiveness, fine-grained control over composite instructions remains challenging due to the

AgentWall: A Runtime Safety Layer for Local AI Agents

arXiv:2605.16265v1 Announce Type: new Abstract: The safety of autonomous AI agents is increasingly recognized as a critical open problem. As agents transition from passive text generators to active ac

AgroCoT: A Chain-of-Thought Benchmark for Evaluating Reasoning in Vision-Language Models for Agriculture

arXiv:2511.23253v3 Announce Type: replace Abstract: Recent advancements in Vision-Language Models (VLMs) have significantly impacted various industries. In agriculture, these multimodal capabilities h

AI Agents May Always Fall for Prompt Injections

arXiv:2605.17634v1 Announce Type: cross Abstract: Prompt injection is the most critical vulnerability in deployed AI agents. Despite recent progress, we show that the prevailing defense paradigm (data

safetyarxiv-cs-cl

AI Alignment Breaks at the Edge

arXiv:2602.20042v2 Announce Type: replace Abstract: General Alignment has improved average-case helpfulness and safety, but current alignment practice still rewards confident, single-turn responses. T

safetyarxiv-cs-cl

AI for Auto-Research: Roadmap & User Guide

arXiv:2605.18661v1 Announce Type: new Abstract: AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents c

AI of the People, by the People, for the People: A Social Choice Approach to Collective Control of Artificial Intelligence

arXiv:2605.16291v1 Announce Type: cross Abstract: With the growing adoption of AI systems, reasoning about how society can exert control over AI becomes an increasingly urgent problem. Existing work o

safetyarxiv-cs-ai