📊 LLM Evaluation - alvin.kuruvilla · Scour

The Coding Assistant Breakdown: More Tokens Please ⚙️MLOps

newsletter.semianalysis.com

·6d·Hacker News

Tokenmaxxing and the search for AI metrics that matter ⚠️AI Safety

leaddev.com·3d·Hacker News

Introducing the Apitally CLI and skill for agents 🤝AI Agents

apitally.io·5d·r/node

Software Engineering Metrics Beyond DORA in 2026 👀Code Review

qasource.com·3d

LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation ✍️Prompt Engineering

CUJBench: Benchmarking LLM-Agent on Cross-Modal Failure Diagnosis from Browser to Backend ⚙️MLOps

Evaluating Strategic Reasoning in Forecasting Agents 🤝AI Agents

garrytan/gbrain-evals ⚙️MLOps

github.com·6d·Hacker News

Measuring the Unmeasurable: Markov Chain Reliability for LLM Agents ⚙️MLOps

BenchGuard: Who Guards the Benchmarks? Automated Auditing of LLM Agent Benchmarks ⚙️MLOps

PMZFX/intel-arc-pro-b70-benchmarks: Benchmark results and performance data for the Intel Arc Pro B70 GPU (Xe2/Battlemage) - LLM inference, video generation, dual-GPU scaling. 📊Profiling

github.com·6d·Hacker News

Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs 📱Edge AI

ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation ⚙️MLOps

Show HN: CSP Benchmarks – Go vs. core.async (Clojure) vs. libgoc (C) 🚀Performance Engineering

github.com·6d·Hacker News

CoRE: A Fine-Grained Code Reasoning Benchmark Beyond Output Prediction 🚀Performance Engineering

Bye Bye Perspective API: Lessons for Measurement Infrastructure in NLP, CSS and LLM Evaluation ⚙️MLOps

The Structured Output Benchmark: A Multi-Source Benchmark for Evaluating Structured Output Quality in Large Language Models ⚙️MLOps

Judging the Judges: A Systematic Evaluation of Bias Mitigation Strategies in LLM-as-a-Judge Pipelines ✍️Prompt Engineering

When Prompt Under-Specification Improves Code Correctness: An Exploratory Study of Prompt Wording and Structure Effects on LLM-Based Code Generation ✍️Prompt Engineering

FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments 🤝AI Agents

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