As large language models (LLMs) gallop ever onwards — including GPT-4, OpenAI’s latest incarnation of the technology behind ChatGPT — scientists are beginning to make use of their power. The explosion of tools powered by artificial intelligence (AI) includes several search engines that aim to make it easier for researchers to grasp seminal scientific papers or summarize a field’s major findings. Their developers claim the apps will democratize and streamline access to research.
But some tools need more refinement before researchers can use them to help their studies, say scientists who have experimented with them. Clémentine Fourrier is a Paris-based researcher who evaluates LLMs at Hugging Face, a company in New York City that develops open-source AI platforms. She used an AI search engine called Elicit, which uses an LLM to craft its answers, to help find papers for her PhD thesis. Elicit searches papers in the Semantic Scholar database ad identifies the top studies by comparing the papers’ titles and abstracts with the search question.
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