Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile
Articles by Ivan Ilin
Training Chemical Plausibility-Aware Large Language Models for Single-Step Retrosynthesis
Get this paper in your agent: hf papers read 2608.18940 Don't have the latest CLI? curl -LsSf https://hf.co/cli/install.sh | bash Models citing this paper 0 No model linking this paper Cite arxiv.org/abs/2608.18940 in a model README.md to link it from this page. Datasets citing this paper 0 No dataset linking this paper Cite arxiv.org/abs/2608.18940 in a dataset README.md to link it from this page.
Computer Science > Machine Learning
Single-step retrosynthesis is a central component of computer-aided synthesis planning, yet its intrinsically one-to-many nature is poorly captured by single-answer evaluation and benchmarking protocols. To address this, we introduce Top-K prompting as a robust training and inference paradigm to better capture diverse, plausible reaction predictions.
Molecular LEGION: incalculably large coverage of chemical space around the NLRP3 target - Scientific Data
Abstract The exploration and mapping of chemical space remain a central challenge in modern drug discovery. Traditional compound libraries and databases cover only a minute fraction of this space, limiting the discovery of novel, bioactive, and patentable chemotypes.
Through knowledge sharing to singularity, accelerated by LLMs
I’ll briefly outline some knowledge-sharing history milestones, the effects open-source had on knowledge accumulation, and the way it brought us to LLMs. Then we’ll stop at the current point to reflect on the effects LLMs will have in tech, science, and society, touching on recent techno-optimism e/acc philosophy that ushers humanity into the bright singularity future.
Chemical Adjustment of Fibrinolysis
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Scratching the Singularity Surface: The Past, Present and Mysterious Future of LLMs
This is an essay with some weekend reflections on the current state of machine learning technology with a particular focus on LLMs aka AI and our current point in history. Before we jump into this exciting singularity thing, I’d like to mention that, as an essay, this is a more personal and less formal writing, sharing my perspective on the Natural Language Understanding evolution and highlighting some ideas that look important in that context.
New Chemicals Suppressing SARS-CoV-2 Replication in Cell Culture
Search Type Submit to this Journal Review for this Journal Edit a Special Issue Article Menu /ajax/scifeed/subscribe Need Help? Support Find support for a specific problem in the support section of our website. Get Support Feedback Please let us know what you think of our products and services. Give Feedback Information Visit our dedicated information section to learn more about MDPI.
Show More
loading
Actions
Is this you?
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Get in touch with Ivan
Contact Ivan, search articles and posts on X, monitor coverage, and track replies from one place.
Learn more about Muck Rack