A while ago, I started working on two R packages for creating 'living reviews': metawoRld and DataFindR, see https://andjar.github.io/metawoRld/articles/conceptual_overv... . You do the broad literature search yourself, but the idea is to use LLMs to select relevant studies and perform data extraction in a structured, reproducible manner. The extracted data is stored in a git repository for collaboration and version tracking, with automated validation and website generation for presenting results.

PaperAI is also an option if you prefer open-source: https://github.com/neuml/paperai

Disclaimer: I'm the primary author of this project.

Check out https://elicit.com/

I built a public literature review search tool for some graduate student friends that became pretty popular in the Santa Barbara area. It actually does exactly what you are describing.

It’s not neural network based: it leverages hierarchical mixture models to give a statistical overview of the data. It lets you build these analysis graphs via search or citation networks.

Example: https://platform.sturdystatistics.com/deepdive?search_type=e...

I've been trying to tackle this exact problem. Current process is to use exa.ai to collect a wide breadth of research papers. Do a summarization pass and convert to markdown. Search for more specific terms then give the relevant papers/context to Gemini 2.5 pro and say give me a summary. Looking for very specific resources and to be honest it's been a terrible process :|

My site, https://www.emergentmind.com, is exactly for this. It surfaces trending AI/ML/CS papers, summarizes them, links to social commentary, lets you read and download papers, links to topics, and more. Would love any feedback you have!

I’ve found a lot of success with https://www.undermind.ai/ though I’m not sure it has the graph you’re looking for

Hi, I'm the creator of https://tatevlab.com. It does something similar + aiming to be something like a "spotify" for research papers (currently working on a feature to allow creating and sharing personal collections). It summarizes papers based on practical potential and you can find papers based on similarity. Feedback is welcome.

https://platform.futurehouse.org/

Connectedpapers.com

emergentmind is pretty good

How do you view o3? I personally find it superior to google search almost always. Do you find that it often misses key references? (also mathematician)

Have you found https://sugaku.net/ useful? It’s focused on math research

This paper is more of a meta-level overview than a hands-on solution

> once LLMs get abandoned

See, you start making a good point in your rant, but then go too much and stop making sense. LLMs are not going to be abandoned. They've "solved" intent from natural language. They're here to stay.

Of course "AI" will get new things. And architectures might improve. And new things will be discovered and added to the tool box. But having the ability to use natural language as input is so invaluable that there's no way we'll just abandon it...

I've been thinking about a plugin that auto-suggests related papers as I write

"AI" is also the opposite of scientific research: word-suggestion algorithm which guess what is the most probable next part given a set of inputs. In the end, you'll still need to prove that your theory is right.