arXiv:2608.23705v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly capable of generating text that challenges human…
Author: script
How GoDaddy transformed its analytics with Amazon Quick
In this post, you will learn how GoDaddy migrated from their legacy business intelligence (BI) tool to Amazon Quick. This was a two-year transformation…
Confidently Wrong, Silently So: Auditing Undetectable Failures of a Deployed On-Device Language Model
arXiv:2608.23663v1 Announce Type: cross Abstract: Aligning deployed language models requires knowing when their outputs can be trusted, yet on-device…
Natera’s intelligent appointment scheduling with Amazon Bedrock AgentCore
Learn how Natera built an automated voice agent on Amazon Bedrock AgentCore that lets patients book mobile phlebotomy appointments through natural…
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…
AI News Brief Hourly Summary 2026-08-26 19h : 19 posts
19 posts published in the last hour 16:33Beyond Executable Models: The Pufibara Agent Harness and the Modelica Agent Workflow Benchmark for Physical System Modeling 16:33Feedback That Backfires: Why Small Language Model Agents Repeat the Call They Just Watched Fail 16:33Preparing…
Beyond Executable Models: The Pufibara Agent Harness and the Modelica Agent Workflow Benchmark for Physical System Modeling
arXiv:2608.23653v1 Announce Type: cross Abstract: AI agents are increasingly used for simulation-driven engineering. Physical system modeling presents…
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…
Preparing data for supervised fine-tuning Part 2: Advanced data strategies
The advanced side of supervised fine-tuning data prep. This second post in a two-part series covers evaluating data readiness with learning curves,…
ToolRobustBench: Stage-Wise Perturbation Evaluation and Failure Diagnosis for Tool-Calling Agents
arXiv:2608.23635v1 Announce Type: cross Abstract: Large language models (LLMs) rely on tool calling as a fundamental agent capability, enabling them to…