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A focused stream of recent stories from the sources curated for this community. Latest: Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation - Nature, Announcing NeurIPS 2025 E2LM Competition: Early Training Evaluation of Language Models, and Getting Started with MLFlow for LLM Evaluation - MarkTechPost. Page 19.
Google News LLM Evaluation
Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation Nature
Hugging Face Evaluation Filter
A Blog post by Technology Innovation Institute on Hugging Face
Google News LLM Evaluation
Getting Started with MLFlow for LLM Evaluation MarkTechPost
METR Blog
METR conducted preliminary evaluations of a set of DeepSeek and Qwen models. We found that the level of autonomous capabilities of mid-2025 DeepSeek models is similar to the level of capabilities of frontier models from late 2024.
METR Blog
Current views on information relevant for visibility into frontier AI risk.
Google News LLM Evaluation
Fine-Tuning LLMOps for Rapid Model Evaluation and Ongoing Optimization | NVIDIA Technical Blog NVIDIA Developer
Hugging Face Evaluation Filter
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
METR Blog
In the last few months, we’ve seen increasingly clear examples of reward hacking on our tasks: AI systems try to “cheat” and get impossibly high scores. They do this by exploiting bugs in our scoring code or subverting the task setup, rather than actually...
Google News LLM Evaluation
Topic: Artificial intelligence (AI) benchmark and training Statista
Google News LLM Evaluation
Moving LLM evaluation forward: lessons from human judgment research Frontiers
Google News LLM Evaluation
Benchmarking LLMs: A guide to AI model evaluation TechTarget
OpenAI Evaluation Filter
HealthBench is a new evaluation benchmark for AI in healthcare which evaluates models in realistic scenarios. Built with input from 250+ physicians, it aims to provide a shared standard for model performance and safety in health.
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