Kurate.org retweeted
ohh this is extremely needed! amazing!
love the filters on top, adding this to my daily workflow!
Kurate.org retweeted
Keeping up with @arxiv is impossible. 500+ preprints a day across dozens of fields.
@KurateOrg scores papers on 16 dimensions (impact, novelty, rigor, surprise, translational...) so you can spot what's worth reading at a glance. Sort, filter & sign up for the weekly newsletter.
Kurate.org retweeted
If AI can reliably help prioritize high-impact research, it could make it much easier for researchers to navigate the growing volume of scientific papers.
The key will be ensuring these rankings complement, rather than replace, expert review.
Kurate.org retweeted
6/ Kurate as a research intelligence platform
We’ll keep improving Kurate by extending the single score ratings into richer dimensions such as reproducibility, difficulty, translational potential, surprisingness, interdisciplinarity and more.
The goal is not to replace deep peer review, but to build a scalable, fast, empirically validated intelligence layer for science.
Stay tuned for more!
Kurate.org retweeted
3/ Kurate was tested in three modes:
- Single Score: directly assign a rating from 0.0 to 10.0 by Claude Opus 4.6 AI to each paper
- Win Rate: pairwise comparisons (matches) using several LLMs aggregated by wins
- TrueSkill: Bayesian ranking from pairwise matches
This allowed Swiss Economics to compare direct scoring vs tournament-style ranking.
All Kurate methods were meaningfully correlated with human expert rankings, but direct scoring (Single Score) was clearly strongest.
Kurate.org retweeted
1/ Swiss Economics (swiss-economics.ch) has validated @KurateOrg's AI scientific paper ranking pipeline against human review data from #ICLR2026.
Full report by @MatthiasHafner1 and @NicolasOderbolz:
swiss-economics.ch/project/i…
Kurate.org is a platform that automatically fetches the latest preprints from @arxiv across 45+ categories (including Machine Learning, Artificial Intelligence, Robotics, Game Theory, Economics, and Physics) and uses LLMs to rank them by scientific impact.
The result: Kurate’s rankings strongly align with expert consensus. Its best method (Spearman correlation 0.71) even exceeds how closely single human reviewers agree with the ground truth (0.56 to 0.68).
just got off a call with @robert_lauko (founder of @LiquityProtocol , @KurateOrg ) and my brain is still processing
we talked about kurate, how pairwise llm tournaments are a better signal for paper quality than citation counts. turns out influencerank and kurate are solving basically the same problem from different directions
then we got into liquity. v1 was already one of the cleanest stablecoin designs, no governance, no oracle manipulation surface, purely collateral-driven. v2 (BOLD) took it further, user-set interest rates, multi-collateral, still immutable. the thesis is that trust in a stablecoin comes from mechanism design, not from a team's promises
the people building the most interesting things in defi are the ones who've already broken something and rebuilt it. robert has done that twice
check out kurate if you haven't @KurateOrg
RT @robert_lauko: I'm thrilled to launch a new Frontiers Research Topic: "Blockchain, DeFi and AI: Economic Systems, Intelligent Agents, an…
Kurate.org retweeted
How emergence happens has long been debated amongst physicists, biologists and philosophers alike. quantamagazine.org/the-new-m…
Kurate.org retweeted
Researchers at Columbia University have developed modular robots that can adapt, repair, and even rebuild themselves using a concept called robot metabolism. 🤖
Instead of remaining fixed, these robots can detach, reconnect, and reorganize their own structure based on the task or environment.
If one part is damaged, the system can replace or rearrange itself rather than stopping completely.
This could reshape the future of disaster response, industrial automation, and even space exploration.
The idea of robots that evolve instead of wear out is becoming more than science fiction.
What real-world application do you think will benefit most from this technology?
🎥 Media: @Columbia
⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.
Kurate.org retweeted

Crémieux@cremieuxrecueilJun 8
🇺🇸
United StatesConnected via United States Android AppAccount-level information, not a live location or per-post device.
Here's an alarming combination of charts:
- CS is the most rapidly growing major degree category
- CS is the degree category that's most rapidly adopting AI
Kurate.org retweeted
Replying to @robert_lauko @KurateOrg
This sounds like a fantastic resource for staying updated on cutting-edge research. Excited to explore the papers and insights from @kurateorg.
Kurate.org retweeted
Replying to @robert_lauko @KurateOrg
That sounds amazing! A fresh take on ranking papers could really elevate research visibility. Can't wait to explore the top picks!
Kurate.org retweeted
if you didn't notice that the paper has been on the arxiv since last year, maybe it's better to leave science to AI
xitter.cf/exosome/status/2056898…
Today we all lost our jobs.....
Three Nature papers showing that scientists in the conventional sense are obsolete
At least read the first one.... the AI replaced all things that the scientist does ....
nature.com/articles/s41586-0…
Kurate.org retweeted
We want to help scientists discover their next breakthrough with AI.
Gemini for Science is our new suite of experimental tools to help them explore more hypotheses, validate work at scale, unpack literature with ease, and more 🧵
Kurate.org retweeted
Replying to @robert_lauko @KurateOrg
Finally a smarter way to discover quality research.
Kurate.org retweeted
Replying to @robert_lauko @KurateOrg
The future of scientific discovery won’t just depend on better researchers.
It’ll depend on better ranking, filtering, and surfacing systems for knowledge itself.
This is a very underrated idea.
Kurate.org retweeted
Replying to @robert_lauko @kurateorg
this is actually a pretty useful idea. arxiv is impossible to follow manually at this point, so even a good first layer of filtering can save a lot of time.






















