
Cohere AI has launched INCLUDE, a comprehensive multilingual language understanding benchmark aimed at addressing cultural and linguistic biases in AI evaluations. The initiative, known as Global-MMLU, spans 42 languages and seeks to provide equitable evaluation across diverse contexts. This benchmark is designed to correct existing imbalances in multilingual AI assessments by introducing a dataset that reflects global cultural sensitivities. Researchers from ByteDance have also released FullStack Bench and SandboxFusion, tools for evaluating large language models (LLMs) in real-world programming scenarios, further contributing to advancements in AI evaluation methodologies.
Multilingual evaluation reimagined: Testing LLMs beyond Western cultural assumptions Global-MMLU addresses cultural biases in multilingual LLM evaluation by introducing a comprehensive benchmark across 42 languages. It identifies that 28% of MMLU questions require… https://t.co/IXt31fs1XH
🧵 1/3 Bytedance AI Research Releases FullStack Bench and SandboxFusion: Comprehensive Benchmarking Tools for Evaluating LLMs in Real-World Programming Scenarios Researchers from ByteDance Seed and M-A-P have introduced FullStack Bench, a benchmark that evaluates LLMs across 11… https://t.co/TRhi3loanY
Global-MMLU 🌎 is trending on @huggingface datasets 🔥 We are very proud of this cross-institutional effort to improve how evaluation reflect contexts all over the world. https://t.co/Q7KkSMkowd https://t.co/c3OVEtFYge https://t.co/YXu5a045GV



