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Researchers from the Allen Institute for AI and the University of Washington have introduced a new benchmark called SUPER. This benchmark is designed to evaluate the capabilities of large language models (LLMs) in autonomously setting up and executing research experiments from research repositories. The initiative emphasizes the importance of reproducibility in scientific research. The SUPER benchmark assesses the performance of various LLMs, including the SWE-agent, which has shown impressive results in these tasks.
An Extensible Open-Source AI Framework to Benchmark Attributable Information-Seeking Using Representative LLM-based Approaches https://t.co/SzofTaIyXK #AI #InformationSeeking #LLM #BusinessTransformation #SalesEngagement #ai #news #llm #ml #research #ainews #innovation #artif… https://t.co/WrxWNzXg41
Allen Institute for AI Researchers Propose SUPER: A Benchmark for Evaluating the Ability of LLMs to Set Up and Execute Research Experiments https://t.co/FkncGFJnz8 #analytics #datascience, #artificialintelligence, #datascience, #datascience #ds, #machinelearning, inoreader
Co-LLM: Learning to Decode Collaboratively with Multiple Language Models 👇🧵 by @MIT_CSAIL #AI #GenAI #LLM https://t.co/KMPh2AlBPa
