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LLM Literature

Project Presentation:

An LLM-powered Slack bot for monitoring LLM literature and AC members' publications (e.g., Heisenberg).

Features:

  • Notifies whenever an AC member publishes a paper.
  • Provides the topics of AC members' papers.
  • Retrieves information from scientific papers.
  • Allows interaction from Slack chat.
  • Monitors and analyzes various types of publications and outputs by Acceleration Consortium Members, including:
    • Peer-reviewed publications in relevant disciplines such as AI and materials science.
    • High-impact publications by citation count and journal impact factor.
    • Non-peer-reviewed scholarly publications, including arXiv submissions.
    • Other scholarly outputs like conference proceedings.
    • Estimations of new compositions of matter, AI algorithms, and datasets shared by members.

Implemented Features:

  • Notification when an AC member publishes a paper.
  • Identifies topics of given papers using a set of keywords.
  • Retrieval-Augmented Generation (RAG) from given papers to extract data (currently in progress).
  • Only working on last publications of the AC members

LLM Literature Scraping

  • Define and focus on publications in relevant disciplines by Acceleration Consortium Members.
  • Relevant Disciplines Include:
    • AI
    • Accelerated materials discovery
    • Self-Driving Labs (SDLs)
    • Autonomous labs
    • High-throughput experimentation
    • High-throughput Density Functional Theory (DFT), etc.
  • Scrape the number of publications in peer-reviewed (non-arXiv) literature.
  • Calculate the annual average over the last 5 years.

High Impact Publications

By Citation Count

  • Identify publications in relevant disciplines that are in the top 10% by citation count across all journals.
  • Calculate the annual average over the last 5 years.

By Journal Impact Factor

  • Identify publications in relevant disciplines that are in the top 10% by journal impact factor.
  • Calculate the annual average over the last 5 years.

Non-Peer-Reviewed Scholarly Publications

  • Count non-peer-reviewed scholarly publications in relevant disciplines, including those on arXiv.
  • Aim to filter out papers that are on both arXiv and published in journals.
  • Calculate the annual average over the last 5 years.

Other Scholarly Creations or Outputs

  • Include scholarly outputs that do not fit typical publication categories, such as conference proceedings.
  • Identify any other outputs found by LLM that don't fit into the above categories.
  • Calculate the annual average over the last 5 years.

New Compositions of Matter

  • Estimate the number of new materials identified in patent applications or published literature by Acceleration Consortium Members.
  • Provide a best estimate or a range for these numbers.
  • Calculate either the annual average over the last 5 years or a total over the previous 5 years.

New AI or Screening Algorithms, Methods, Workflows, Models

  • Estimate the number of new AI/screening algorithms, methods, workflows, or models identified in patent applications or published literature by Acceleration Consortium Members.
  • Provide a best estimate or a range for these numbers.
  • Calculate either the annual average over the last 5 years or a total over the previous 5 years.
  • Estimate the number of datasets related to AI and materials released to the public by Acceleration Consortium Members.
  • Provide a best estimate or a range for these numbers.
  • Calculate either the annual average over the last 5 years or a total over the previous 5 years.

Code Overview

Author object:

  • Takes as input the name of an AC author
  • Has the ability to fetch their last publication
    • Uses the scholarly API to get the data (filled)
  • Updates a json file with the data it had about the publication

The Publication object:

  • Takes as input a publication filled (output of a scholarly)
  • Gets data such as the year of publication, abstract, link etc...
  • Uses a LLM on the abstract to get the topics of the publication (Updating it)
  • Uses webscrapping of the scholarly home page of the author to get the link to the PDF of the publication (if found - Working on it)

RAG use - still working on it:

  • Embedding used: fast emnbedding (updating it to Ollama's)
  • Getting pertinent information from the PDF

Bot object:

  • Runs a Slack bot which is able to send messages and respond to slack slash(/) commands

Metadata

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