Large Language Models (LLMs) are pivotal for advancing machines' interactions with human language, performing tasks such as translation, summarization, and question-answering. However, evaluating their performance can be daunting due to the need for substantial computational resources.
A major issue encountered while evaluating LLMs is the significant cost of using large benchmark datasets. Conventional benchmarks like HELM…
Harvard researchers have launched ReXrank, an open-source leaderboard that aims to improve artificial intelligence (AI)-powered radiology report generation. This development could revolutionize healthcare AI, especially concerning chest X-ray image interpretation. ReXrank aims to provide a comprehensive, objective evaluation framework for advanced AI models, encouraging competition and collaboration among researchers, clinicians, and AI enthusiasts and accelerating…
Harvard researchers have won the medical AI field's attention with their launch of ReXrank, an open-source leaderboard promoting the advancement of AI-driven radiology report generation, particularly in chest X-ray imaging. This unveiling implicates changes in healthcare AI and is designed to bring a transparent and full-picture evaluation framework.
ReXrank makes use of a variety of datasets…
The article introduces a benchmark known as ZebraLogic, which assesses the logical reasoning capabilities of large language models (LLMs). Using Logic Grid Puzzles, the benchmark measures how well LLMs can deduce unique value assignments for a set of features given specific clues. The unique value assignment task mirrors those that are often found in assessments…
The OpenGPT-X team has launched the European Large Language Models (LLM) Leaderboard, a key step forward in the creation and assessment of multilingual language models. The project began in 2022 with backing from the BMWK and the support of TU Dresden and a 10-partner consortium comprised of numerous sectors. The primary target is to expand…
Hugging Face has unveiled the Open LLM Leaderboard v2, a significant upgrade to its initial leaderboard used for ranking language models. The new version aims to address the challenges faced by the initial model, featuring refined evaluation methods, tougher benchmarks, and a fairer scoring system.
Over the last year, the original leaderboard had become a…
Hugging Face has released a significant upgrade to its Leaderboard for open-source language models (LLMs) geared towards addressing existing constraints and introducing better evaluation methods. Notably, the upgrade known as Open LLM Leaderboard v2 offers more stringent benchmarks, presents advanced evaluation techniques, and implements a fairer scoring system, fostering a more competitive environment for LLMs.
The…
Artificial Analysis has launched the Artificial Analysis Text to Image Leaderboard & Arena, an initiative aimed at evaluating the effectiveness of AI image models. The initiative compares open-source and proprietary models, seeking to rate their effectiveness and accuracy based on the preferences of humans. The leaderboard, updated with ELO scores compiled from over 45,000 human…
BigCode, a leading developer of large language models (LLMs), has launched BigCodeBench, a new benchmark for comprehensively assessing the programming capabilities of LLMs. This concurrent approach addresses the limitations of existing benchmarks like HumanEval, which has been criticized for its simplicity and scant real-world relevance. BigCodeBench comprises 1,140 function-level tasks which require the LLMs to…