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+have+shown+remarkable+performance+on+many+tasks+in+different+domains.+However%252C+their+performance+in+closed-book+biomedical+machine+reading+comprehension+(MRC)+has+not+been+evaluated+in+depth.+In+this+work%252C+we+evaluate+GPT+on+four+closed-book+biomedical+MRC+benchmarks.+We+experiment+with+different+conventional+prompting+techniques+as+well+as+introduce+our+own+novel+prompting+method.+To+solve+some+of+the+retrieval+problems+inherent+to+LLMs%252C+we+propose+a+prompting+strategy+named+Implicit+Retrieval+Augmented+Generation+(RAG)+that+alleviates+the+need+for+using+vector+databases+to+retrieve+important+chunks+in+traditional+RAG+setups.+Moreover%252C+we+report+qualitative+assessments+on+the+natural+language+generation+outputs+from+our+approach.+The+results+show+that+our+new+prompting+technique+is+able+to+get+the+best+performance+in+two+out+of+four+datasets+and+ranks+second+in+rest+of+them.+Experiments+show+that+modern-day+LLMs+like+GPT+even+in+a+zero-shot+setting+can+outperform+supervised+models%252C+leading+to+new+state-of-the-art+(SoTA)+results+on+two+of+the+benchmarks.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.14ef4c56023832292a8d3f03bbcd09aa%3frik%3db3wGVWjBkOGZrw%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=GPT+and+AI+in+Biomedical+Science&FORM=IRPRST&ck=C47BD9F8C6A9E566FD479BD3C6723CEC&selectedIndex=9&itb=0)
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