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AI assessment

4 articles · Page 1 of 1
Woodpecker Software Testing
Woodpecker Software Testing
Aug 23, 2026 · Artificial Intelligence

How to Choose the Right Model Evaluation Method – From Exact Match to LLM-as-a-Judge

This guide explains objective metrics such as Exact and Fuzzy Match, the QUEST framework for human evaluation, rubric design and calibration, the LLM-as-a-Judge approach with its biases and trade‑offs, and a five‑dimensional evaluation framework for building robust, explainable and fair AI systems.

AI assessmentLLM-as-a-JudgeRubric
0 likes · 26 min read
How to Choose the Right Model Evaluation Method – From Exact Match to LLM-as-a-Judge
Data Party THU
Data Party THU
Mar 2, 2026 · Artificial Intelligence

How ReLE Redefines Chinese LLM Evaluation and Reveals Capability Anisotropy

The ReLE framework introduces a dynamic, variance‑aware evaluation system that diagnoses capability anisotropy across 304 Chinese large language models, exposing ranking instability, commercial‑vs‑open‑source gaps, and format barriers while cutting evaluation cost by 70%.

AI assessmentCapability anisotropyChinese LLMs
0 likes · 9 min read
How ReLE Redefines Chinese LLM Evaluation and Reveals Capability Anisotropy
Huolala Tech
Huolala Tech
Dec 31, 2024 · Artificial Intelligence

How Huolala Built LaLaEval: A Practical Framework for Large Model Evaluation

Huolala shares its LaLaEval framework, detailing how large‑model applications are evaluated through defined stages—background analysis, metric design, dataset generation, standards setting, and statistical analysis—while illustrating real‑world use cases in freight and driver invitation scenarios, and outlining future automation prospects.

AI assessmentlarge model evaluationlogistics AI
0 likes · 26 min read
How Huolala Built LaLaEval: A Practical Framework for Large Model Evaluation
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Jul 26, 2023 · Industry Insights

Human‑Perception‑Based End‑Cloud Super‑Resolution: Cutting Bandwidth, Boosting Quality

The LiveVideoStackCon 2023 session revealed how a human‑perception‑driven end‑cloud super‑resolution framework, AI‑based no‑reference video quality assessment, and rigorous AB‑testing methods can dramatically reduce video bandwidth while enhancing visual quality, illustrating the broader challenges and opportunities in modern audio‑video systems.

AB TestingAI assessmentaudio-video industry
0 likes · 13 min read
Human‑Perception‑Based End‑Cloud Super‑Resolution: Cutting Bandwidth, Boosting Quality