And this isn’t even really a great application for RAG. Papermaps just goes off of references and citations. Perhaps a sentiment analysis would be marginally useful, but since you need a human to verify all LLM outputs it would be a dubious time savings.
The system scores review papers very favorably and the “yes/no/maybe” conclusion is right in the abstract, usually the last sentence or two of it. This is not a prime candidate for any LLM, it’s simple database operations on srtuctured data that already exists. There’s no use case here.
Perhaps a sentiment analysis would be marginally useful, but since you need a human to verify all LLM outputs it would be a dubious time savings.
Thank you, yes. That’s exactly my point. You’d need a human to verify all of the outputs anyways, and these are literally machines that exclusively make text that humans find believable, so you’re likely adding to the problem of humans messing stuff up moreso than speeding anything up. Being wrong fast has always been easy, so it’s no help here.
And this isn’t even really a great application for RAG. Papermaps just goes off of references and citations. Perhaps a sentiment analysis would be marginally useful, but since you need a human to verify all LLM outputs it would be a dubious time savings.
The system scores review papers very favorably and the “yes/no/maybe” conclusion is right in the abstract, usually the last sentence or two of it. This is not a prime candidate for any LLM, it’s simple database operations on srtuctured data that already exists. There’s no use case here.
Thank you, yes. That’s exactly my point. You’d need a human to verify all of the outputs anyways, and these are literally machines that exclusively make text that humans find believable, so you’re likely adding to the problem of humans messing stuff up moreso than speeding anything up. Being wrong fast has always been easy, so it’s no help here.