Live data from Hacker News

Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

news.ycombinator.com

71–80 of 134 posts

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#72
post #71

I really, really wish you would use a different citation format. Arbitrary numbers are really the least information. At least use last names and years, so I can have some idea which paper you are talking about without scrolling back and forth.

Thanks! That's helpful to hear. Honestly just did numbers because the LLM has no trouble remembering which is which, and it's easier to programmatically parse out the citations to build hyperlinks (compared to names/years, where little variations creep in).

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#73
Very impressed. I am not a scientist but am building a product for intent-based discounting in Shopify. Typically Google scholar gives me very generic results using LSTM etc however this search gave me some interesting results with focus on real world implementation. The clarifying questions are also quite impressive as it gives the impression that it is understanding the query really well. Good stuff. I think it might be useful for end-users and not just company/research folks as well

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#74
I tried this with a question for an area I know well. It's pretty impressive but missed some key references.

I'd love to see limitations like this quantified and clearly flagged. Otherwise there's a danger that people may the assume results are definitive, and this could have the opposite outcome to that intended (much time spent working on something only to disocver it's been done already).

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#76
post #74

I tried this with a question for an area I know well. It's pretty impressive but missed some key references. I'd love to see limitations like this quantified and clearly flagged. Otherwise there's a danger that people may the assume results are definitive, and this could have the opposite outcome to that intended (much time spent working on something only to disocver it's been done already).

Yes, this is one of the most important aspects of the tool; in cases where you care about getting everything, make sure to take a look at the estimated percent of papers found at the bottom of the summary section. That gives you a sense of how complete the set of references likely are. We've tuned it to get around half of the total papers for the "median" user query on a first pass. If users desire, they can "extend" the search to have Undermind look for more papers. Additional caveat to remember with the current system is that it only accesses abstracts, so if you'd need to look in the full text to know a work is relevant, we wouldn't be able to catch it.

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#77
post #74

I tried this with a question for an area I know well. It's pretty impressive but missed some key references. I'd love to see limitations like this quantified and clearly flagged. Otherwise there's a danger that people may the assume results are definitive, and this could have the opposite outcome to that intended (much time spent working on something only to disocver it's been done already).

Yes, this is one of the most important aspects of the tool; in cases where you care about getting everything, make sure to take a look at the estimated percent of papers found at the bottom of the summary section. That gives you a sense of how complete the set of references likely are. We've tuned it to get around half of the total papers for the "median" user query on a first pass. If users desire, they can "extend"…

Thanks for clarifying. I didn't appreciate that it only searches abstracts. That might explain some of the missing references. Anyway, great work, will look forward to using it more.

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#78
My first impression is that it’s quite cool, but it should weight things by importance to some degree.

I tried a search on my previous research area (https://www.undermind.ai/query_app/display_one_search/5408b4...) and it missed some key theoretical papers. At the same time, it picked up the three or four papers I’d expected it to find plus a PhD thesis I expected it to find. The results at the top of the list though are very recent and one of them is on something totally different to what I asked it for (“Skyrmion bubbles” != “Skyrmions”). The 7th result is an absolutely core paper, would be the one I’d give to a new PhD student going into this area and the one I’d have expected it to push up to the top of the list.

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#79
post #77

Earlier quoted context omitted.

Yes, this is one of the most important aspects of the tool; in cases where you care about getting everything, make sure to take a look at the estimated percent of papers found at the bottom of the summary section. That gives you a sense of how complete the set of references likely are. We've tuned it to get around half of the total papers for the "median" user query on a first pass. If users desire, they can "extend"…

Thanks for clarifying. I didn't appreciate that it only searches abstracts. That might explain some of the missing references. Anyway, great work, will look forward to using it more.

Yep, will add in full texts as we can in the future. Let me know if the percent of papers found as an indication of an exhaustiveness measure was clear? Reach out to us at support@undermind.ai if you'd be willing to provide more feedback on your experience.

Re: Launch HN: Undermind (YC S24) – AI agent for discovering scientific papers

#80
post #12

Very cool, and very relevant to my life -- I am currently writing a meta-analysis and finishing my literature search. I gave it a version of my question, it asked me reasonable follow-ups, and we refined the search to: > I want to find randomized controlled trials published by December 2023, investigating interventions to reduce consumption of meat and animal products with control groups receiving no treatment, measu…

[deleted]
Post reply on HN