#ai-evaluation

ALL ABOUT AI EVALUATIONS— AGENT EVAL S— EVAL DRIVEN DEVELOPMENT

As Agents and Agentic AI Development is picking up traction, the need of AI Evals is also increasing. Good evaluations helps businesses and…

Why Consistency Matters More Than Average AI Accuracy

Average AI performance can be misleading. A model that’s brilliant once but unreliable the next time may never be ready for real business…

AlphaEvolve Broke a 56-Year-Old Math Record. It Still Can’t Touch Your Codebase.

For 56 years, nobody beat Volker Strassen.

Refusal Is a Feature: What LLM Evaluation Misses When It Only Measures Accuracy

In high-stakes domains, the question your system refuses to answer matters more than the ones it gets right.

It’s the Rail, Not the Model: A 7-Model Factorial on LLM Financial Hallucination

Packet 1: IMMB-NS Verification and the Dynamic Blanket Stress Test

Empirical Engagement Packet for Testing the Synchronization Condition

What are AI Evals and Why They Matter (It’s Not Just Testing)

The world of AI is moving fast. Models like GPT-5.x, Claude, and Gemini are no longer just answering questions, as they’re writing…

Stop Fighting Unreliable AI Agent Evals, Use a Stunt Double Instead

How the testing instincts we had for regular software led us to build an open source mocking framework for AI agents.

I Was Wrong: Free Local LLMs Can Go Round-for-Round With Claude and ChatGPT on Real-World Tasks

Gemma 4 crushed writing and Qwen 3.6 matched Claude in research. Here is how local models really stack up.

30–26: [知識] AI Application Evaluation ( 2 ) 之 Ragas 評分指標 ( Langfuse 版本 )

上一篇文章我們談論完 Evaluation 中的評估方式以後，接下來我們將要談論 :

Evaluation Layer for AI Systems: The Engine of Trusted Enterprise AI

Most AI teams evaluate models.

Why Gold Standard Evaluation Sets Are the Key to Reliable Enterprise AI Evaluation

Enterprises rely more than ever on AI to make decisions, automate tasks, and improve efficiency. However, even the most advanced AI models…

A Single Character Beat 890 AI Tasks. The Benchmark Never Noticed.

Berkeley researchers built an agent that achieved near-perfect scores across every major AI benchmark without solving anything. The deeper…

Reference Architecture for AI Evaluation at Scale

Right now, most enterprise AI teams are obsessing over the exact same wrong question:

How to Evaluate OpenAI Responses API Prompts With Web Search

The OpenAI Responses API lets your prompts search the web in real time. Your model can pull live data, check current facts, and ground its…

AI Agent Evaluations: Building Trust for Success

Explore why comprehensive AI agent evaluations, focusing on user interaction and trust, are crucial for successful deployment.

Run Stanford MedHELM on Any vLLM Model with One Bash Script

What Is HELM?

Evaluate Your Large Language Model

✍️ Co-Authors: 1. Nishit Rana 2. Ayushi 3. Aman Mundra

Enterprise-Grade AI Platforms Built for Scale and Resilience

Enterprise-grade AI platforms are no longer experimental environments. They are the backbone of scalable AI systems, production-ready AI…

Reliable LLM Evals That Actually Work — The 2026 Practical Playbook

Tools, Psychometrics & Adaptive Evaluation Techniques

Accumulation Metrics (P6)

Persistent Reasoning: Practical Exploration | How to measure accumulation without inspecting structure

Bridging Operations Research and Generative AI: Evaluating Multi-Agent Systems for Pricing…

Introduction

Measuring Success in AI Products: Beyond Accuracy Metrics

The Complete Guide to LLM Judge Models: G-Eval and Beyond

Imagine having a tireless, consistent expert evaluator that can assess thousands of AI outputs in minutes, with the nuance of a human but…

4 Powerful Metrics For Testing AI Model Performance [2025]

A Guide to Accuracy, Precision, Recall, F1-Score, and AUC-ROC with Real-World Examples

REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once (REST: 한 번에 여러 문제를…

Understanding AI Evals: The Backbone of Trustworthy Generative AI

As the race to deploy Generative AI accelerates, the importance of robust, structured evaluations , collectively referred to as AI Evals…

A Boring but Practical 10-Step Guide to Data Labeling & Evaluation

Below is a very terse and opinionated set of steps to data labeling and model evaluation.