Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T16:00:23.257212Z
Paper Citation Record · LEDGER
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
As of 20 August 2026, this Paper Citation Record lists 100 of 235 outbound references and 7 inbound Pith citation observations for arXiv:2411.15221.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T16:59:32.862419Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
100 of 235 outbound references displayed
- verified exact12
- verified fuzzy0
- unresolved88
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
4
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation ff2e8eea-9386-4fb6-8364-b682b185f029 · outbound
This paper cites Nolte, L.
Reference 1
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.428336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 98d5bb40-80db-4b66-bd7e-1a416fd905f4 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 2
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.416051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d1961e30-9e77-45f9-a21e-7729bb37dccf · outbound
This paper cites Heller, A.
Reference 3
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.403476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 44f8aa82-6abc-41f8-b2c1-8cb62dd3d1f1 · outbound
This paper cites Can Large Language Models Empower Molecular Property Prediction?.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Can Large Language Models Empower Molecular Property Prediction?
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.825974Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0bf2da35-8c12-4b7a-87be-dcad9175a30e · outbound
This paper cites Regression with Large Language Models for Materials and Molecular Property Prediction.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Regression with Large Language Models for Materials and Molecular Property Prediction
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.830364Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce791821-7f5a-4d7f-ac95-93b8fafdf5bb · outbound
This paper cites Vacareanu, V.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Vacareanu, V
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.835334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6eba37d0-eabb-4782-ad39-c5754c01dce1 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 8
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.384754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0819bac8-e11c-477f-91b6-9db77a1d3a6b · outbound
This paper cites Lu and Y.
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.849428Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc48beb4-3652-4f07-8228-7f7de32a6f67 · outbound
This paper cites Bhattacharya, H.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Bhattacharya, H
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.853462Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0daa6041-949e-4a0c-af46-99274594cf65 · outbound
This paper cites Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.857335Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b8a59724-bf90-40c6-a715-3357c9e7929e · outbound
This paper cites LLMatDesign: Autonomous Materials Discovery with Large Language Models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry LLMatDesign: Autonomous Materials Discovery with Large Language Models
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.861506Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef8926fc-fde0-43ec-9176-999e272eb16d · outbound
This paper cites Can LLMs Generate Diverse Molecules? Towards Alignment with Structural Diversity.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Can LLMs Generate Diverse Molecules? Towards Alignment with Structural Diversity
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.865581Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dbed0cf-da69-43fa-b824-0b5b692b2422 · outbound
This paper cites Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge of Large Language Models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge of Large Language Models
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.869921Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90f45004-e5e7-4bda-8fe9-313196e6281f · outbound
This paper cites Kristiadi et al., in Proceedings of the 41st International Conference on Machine Learning, PMLR, 2024, vol.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Kristiadi et al., in Proceedings of the 41st International Conference on Machine Learning, PMLR, 2024, vol
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.874175Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ebd7a8d-b72c-4329-aada-08480ebdeee7 · outbound
This paper cites Are LLMs Ready for Real-World Materials Discovery?.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Are LLMs Ready for Real-World Materials Discovery?
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.878300Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c5765c6b-ef5a-439f-83fb-328a8e1e331c · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.882095Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e789566a-dfe8-43ee-87e9-849840eb0310 · outbound
This paper cites The Llama 3 Herd of Models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry The Llama 3 Herd of Models
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.895207Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f047f6c-817e-4b9f-bec0-0c7edf302d91 · outbound
This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.899082Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 042f9e6f-58ea-4def-8f35-2dc731bb380b · outbound
This paper cites ChemCrow: Augmenting large-language models with chemistry tools.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry ChemCrow: Augmenting large-language models with chemistry tools
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.903881Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18305987-cd9e-43cb-a170-3e7755aebc70 · outbound
This paper cites RestGPT: Connecting Large Language Models with Real-World RESTful APIs.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry RestGPT: Connecting Large Language Models with Real-World RESTful APIs
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.908161Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bada4e22-9343-42c9-bc4d-1ea99b208038 · outbound
This paper cites HoneyComb: A Flexible LLM-Based Agent System for Materials Science.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry HoneyComb: A Flexible LLM-Based Agent System for Materials Science
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.912116Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03a48048-159f-488c-80c1-caae76466c9e · outbound
This paper cites ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.919916Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c82d5f8c-c89a-4cdb-ad97-9796bd12b28a · outbound
This paper cites Tom et al., Chem.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Tom et al., Chem
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.924021Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aa852270-dde1-469b-9dca-fc2b974d64c8 · outbound
This paper cites Chase, Langchain, 2024.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Chase, Langchain, 2024
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.927751Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 94a0f2dc-db37-42a3-b86b-70cc5ac91720 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.931427Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05fd98e3-928f-497c-a772-8b2dca00f435 · outbound
This paper cites Yan et al., Br.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Yan et al., Br
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.937049Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8665a22-ad83-44ed-bf99-127b4464a4fc · outbound
This paper cites Large Language Models for Education: A Survey and Outlook.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Large Language Models for Education: A Survey and Outlook
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.943984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6db16d1-74bd-497d-bb6f-d39304bff3a7 · outbound
This paper cites Kasneci et al., Learn.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Kasneci et al., Learn
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.949331Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 270b709a-04fb-4eb6-a243-c353854d56df · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 34
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.314165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2a0ce7f7-ab86-40ea-96ae-67b2f8062b7e · outbound
This paper cites MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.957864Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c0ec3f22-e703-4d92-9ef2-2638589c9c3a · outbound
This paper cites https://assets.anthropic.com/m/61e7d27f8c8f5919/original/Claude-3-Model-Card.pdf.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry https://assets.anthropic.com/m/61e7d27f8c8f5919/original/Claude-3-Model-Card.pdf
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.961812Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 828e05af-3e47-4948-9f0b-67dae1fa19a1 · outbound
This paper cites Mixtral of Experts.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Mixtral of Experts
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.965690Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53e129ed-812d-4faa-a739-c9fbc1697c92 · outbound
This paper cites Draxl and M.
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.970746Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a2db3be-793b-4b10-ab94-ca932d8dc8d3 · outbound
This paper cites Robust Speech Recognition via Large-Scale Weak Supervision.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Robust Speech Recognition via Large-Scale Weak Supervision
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.975026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78e96226-a3fe-413c-bd38-d10ae2624ec0 · outbound
This paper cites Hypothesis Generation with Large Language Models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Hypothesis Generation with Large Language Models
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.979237Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f886ef40-eee1-473d-9b43-9d9ca45c1796 · outbound
This paper cites Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.983545Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed7fc9a5-edf3-4a29-8d97-a44cda5529e0 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.987579Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5353a3c8-3bbb-49d0-81af-79f0b3d31938 · outbound
This paper cites Harnessing the Power of Adversarial Prompting and Large Language Models for Robust Hypothesis Generation in Astronomy.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Harnessing the Power of Adversarial Prompting and Large Language Models for Robust Hypothesis Generation in Astronomy
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.991619Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea424e88-6afc-478e-b878-8d0fbb448bbc · outbound
This paper cites Beyond designer's knowledge: Generating materials design hypotheses via large language models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Beyond designer's knowledge: Generating materials design hypotheses via large language models
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:22.996656Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f318846-7153-4d43-a39a-d6a59a5b851d · outbound
This paper cites Shir, ChemRxiv, 2024.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Shir, ChemRxiv, 2024
Reference 45
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.288834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4650a199-f25f-4767-b2e3-5a8b1358542a · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.005722Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 096bb599-6d49-4745-ac8b-71c57fe25f18 · outbound
This paper cites Large Language Models for Scientific Information Extraction: An Empirical Study for Virology.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Large Language Models for Scientific Information Extraction: An Empirical Study for Virology
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.009979Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 174187bc-58eb-47a9-94f9-74a126fcfd46 · outbound
This paper cites Dagdelen et al., Nat.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Dagdelen et al., Nat
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.014151Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8621e19-a519-4277-ad57-1e666acd5687 · outbound
This paper cites Large Language Models for Generative Information Extraction: A Survey.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Large Language Models for Generative Information Extraction: A Survey
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.018460Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation afa364e4-69bf-4aa9-8be8-07b942fc8fc7 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.022437Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12110391-2818-49bb-a53f-5cdda3da4674 · outbound
This paper cites SciAgent: Tool-augmented Language Models for Scientific Reasoning.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry SciAgent: Tool-augmented Language Models for Scientific Reasoning
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.026198Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c6820e5-ba5e-4247-b544-9572a2a463f9 · outbound
This paper cites GPT-4 Technical Report.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry GPT-4 Technical Report
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.030162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e6bde3b-c8a6-4e92-8d10-41bbe8f5c35c · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.038102Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d27fa941-7db0-4f7f-9aa6-79dddc4f5c71 · outbound
This paper cites Choudhary, J.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Choudhary, J
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.041963Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 09547880-3ef0-4eca-91ce-66990fc2a3f9 · outbound
This paper cites Petretto, S.
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.045773Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 17e7e874-5943-40e0-a9b2-752285e89152 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.049457Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 64f64c22-3200-4bd6-8811-8d2afdd92b57 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.053180Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b08abcf-721f-43f2-a934-86dd22524fc6 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 59
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.256176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cd93675a-be7c-4f4a-8dc4-1d569d3a2dda · outbound
This paper cites LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.061421Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db78f720-9e78-4ddc-aabd-7eab8be7e7cb · outbound
This paper cites Multimodal Foundation Models for Material Property Prediction and Discovery.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Multimodal Foundation Models for Material Property Prediction and Discovery
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.065712Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6737db2-f327-4a0a-a176-d09c6f67ec4c · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.070038Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f55b8d2d-eab6-47e6-9187-b43253b30173 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 63
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.223167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 25587ed9-be16-4e7d-845f-25a9ab2c0506 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.078049Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ffbd5d7c-6f0f-4f98-b365-75f2f8f625b1 · outbound
This paper cites Raffel, N.
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.081687Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36a3df82-89d7-43e9-abef-7656beb3e8a3 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 66
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.085174Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 86a3855d-6d97-4c3b-9a47-4a02f6399a8d · outbound
This paper cites Goodall, A.
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.089199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f78c1c7-63cc-4030-a5a8-85dff2270dbf · outbound
This paper cites Trewartha, et al., 'Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science', Patterns, vol.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Trewartha, et al., 'Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science', Patterns, vol
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.093190Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf024131-a722-4a50-99c0-bfe6b827560e · outbound
This paper cites Gupta, et al., MatSciBERT: A materials domain language model for text mining and information extraction, npj Computational Materials, vol.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Gupta, et al., MatSciBERT: A materials domain language model for text mining and information extraction, npj Computational Materials, vol
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.097477Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 763a9e41-2b63-4dac-a785-fc5eb93dc90c · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 70
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.101649Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62e7beba-73f9-43a6-a4ad-92f1c7063670 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 71
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.106064Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71fe8c90-097b-4a2a-bb1b-5a61324e05f3 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.110114Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a307354-a786-4d83-82ba-0f1cd7226c27 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 73
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.114998Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 181dd469-eb83-4048-868f-2ca96c9fb0b6 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.120157Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bdfd0247-87dd-4112-b4a4-ff35f494330a · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.124060Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fbf8aba-865f-4a01-a232-458ce2059b57 · outbound
This paper cites M., Ai, Q., Al-Feghali, A., Badhwar, S., Bocarsly, J.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry M., Ai, Q., Al-Feghali, A., Badhwar, S., Bocarsly, J
Reference 77
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.131762Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 409aa136-7ef6-4069-88db-ea2b513d1be1 · outbound
This paper cites Less can be more for predicting properties with large language models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Less can be more for predicting properties with large language models
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.135235Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1eca16a-515e-40b5-9492-e6b7dd1fb3bb · outbound
This paper cites P., Kornbluth, M.,.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry P., Kornbluth, M.,
Reference 79
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.139256Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 78f56d54-bf94-4025-a4b1-0204b3a3659c · outbound
This paper cites K., & Raghavachari, K.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry K., & Raghavachari, K
Reference 80
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.142956Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 793d1c9a-0ed6-49c9-9a9e-d06fd52b867a · outbound
This paper cites In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry In-Context Learning of Physical Properties: Few-Shot Adaptation to Out-of-Distribution Molecular Graphs
Reference 81
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.146503Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ffcd6a9-e88f-4a5a-a647-f6c0280f11ef · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.150533Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ca5375f-b253-4521-8e4a-4f2ba0589b5d · outbound
This paper cites T., Kabylda, A., Sauceda, H.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry T., Kabylda, A., Sauceda, H
Reference 83
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.154229Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 22a843fc-1252-455c-8a4d-fd8f72ea94e7 · outbound
This paper cites M., Qu, C., Conte, R., Nandi, A., Houston, P.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry M., Qu, C., Conte, R., Nandi, A., Houston, P
Reference 84
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.158368Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c99beedf-0e7d-40a7-a4dc-7d8538f84713 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 85
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.162263Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7aa520c2-fd24-4bd1-a0dd-e6952da9d3d6 · outbound
This paper cites P., Simm, G., Ortner, C., & Csányi, G.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry P., Simm, G., Ortner, C., & Csányi, G
Reference 86
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.165941Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4de247b-6efb-4f60-ae30-804bf6c34260 · outbound
This paper cites A., ACS Central Sci., 2019, Vol.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry A., ACS Central Sci., 2019, Vol
Reference 87
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.169864Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb50f835-6267-41f4-baba-12b69d2e5d2f · outbound
This paper cites C., ChemRxiv Preprint.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry C., ChemRxiv Preprint
Reference 88
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.196443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation bb4b32de-387c-4adf-91ae-ab79b330d437 · outbound
This paper cites https://sdbs.db.aist.go.jp.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry https://sdbs.db.aist.go.jp
Reference 90
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.182300Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 768d11ed-2df1-4a6b-9314-6bae3ab8dc9b · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 91
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.184738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 404332d7-429c-43a1-b1c3-40f8229855c6 · outbound
This paper cites an unresolved cited work.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Unresolved cited work
Reference 92
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.189938Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b1ddab1-cb4b-45b0-b426-f76e85377742 · outbound
This paper cites Cyclic peptides for drug development,.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Cyclic peptides for drug development,
Reference 93
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.194477Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31e40ef1-f6c9-4eb0-b399-03f2722190c1 · outbound
This paper cites De novo development of small cyclic peptides that are orally bioavailable,.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry De novo development of small cyclic peptides that are orally bioavailable,
Reference 94
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.349526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 386af33c-03ed-491d-89e8-6e2f4548f4d1 · outbound
This paper cites Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation
Reference 95
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.202984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 94223d3d-f50a-4cfb-a966-a2380b8c5337 · outbound
This paper cites A Survey on In-context Learning.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry A Survey on In-context Learning
Reference 96
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.207669Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93c4a36d-4cb1-4210-ba3d-00383724e437 · outbound
This paper cites Many-Shot In-Context Learning.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Many-Shot In-Context Learning
Reference 97
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.211837Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d9bcbb5-95c2-4896-aaa2-34182293a27e · outbound
This paper cites A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Reference 98
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.215760Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f80af05d-5171-4bad-8dc7-c0d0ce65b9d3 · outbound
This paper cites A Detailed Investigation on Conformation, Permeability and PK Properties of Two Related Cyclohexapeptides,.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry A Detailed Investigation on Conformation, Permeability and PK Properties of Two Related Cyclohexapeptides,
Reference 99
- Resolution
- verified exact
- doi, observed 2026-08-12T16:00:24.173255Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d72edde8-a220-410b-93ab-4226246271c1 · outbound
This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Reference 100
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.223353Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7a22ca2-8d7f-4275-8441-f7bac8f7982a · outbound
This paper cites Reducing hallucination in structured outputs via Retrieval-Augmented Generation.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Reducing hallucination in structured outputs via Retrieval-Augmented Generation
Reference 101
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.226827Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29e6d42f-72d1-46fd-a74b-319d280d4aca · outbound
This paper cites Review on applications of metal–organic frameworks for co2 capture and the performance enhancement mechanisms.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Review on applications of metal–organic frameworks for co2 capture and the performance enhancement mechanisms
Reference 102
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.231425Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6b9e3222-14bb-4afe-840e-9e2738d9686b · outbound
This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry ReAct: Synergizing Reasoning and Acting in Language Models
Reference 103
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.236391Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bac90623-ce55-4760-ab89-c5f45b60fdf9 · outbound
This paper cites dZiner: Rational Inverse Design of Materials with AI Agents.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry dZiner: Rational Inverse Design of Materials with AI Agents
Reference 104
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.240739Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7b909e9-96b3-4673-b82b-bc833a21252a · outbound
This paper cites Semiconductor metal–organic frameworks: future low- g"bandgap materials.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Semiconductor metal–organic frameworks: future low- g"bandgap materials
Reference 105
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.244975Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53d007db-b0ef-441d-9294-6513d243344e · outbound
This paper cites Band gap modulations in uio metal–organic frameworks.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Band gap modulations in uio metal–organic frameworks
Reference 106
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.249242Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4c41b683-bf6b-497e-8a72-84c81331b25e · outbound
This paper cites Band gap engineering of paradigm mof-5.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Band gap engineering of paradigm mof-5
Reference 107
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.253254Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31f6702f-11d4-4073-afbc-4ef4a0187b2a · outbound
This paper cites Theoretical investigations on the chemical bonding, electronic structure, and optical properties of the metal- organic framework mof-5.
Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry Theoretical investigations on the chemical bonding, electronic structure, and optical properties of the metal- organic framework mof-5
Reference 108
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T16:00:23.257212Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 4644a32e-6b1f-4e33-849e-48ca76f73384 · inbound
Foundational Large Language Models for Materials Research cites this paper.
Foundational Large Language Models for Materials Research Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T16:59:32.862419Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73602e7a-d19d-4395-a25d-b129da1d84d8 · inbound
Multicrossmodal Automated Agent for Integrating Diverse Materials Science Data cites this paper.
Multicrossmodal Automated Agent for Integrating Diverse Materials Science Data Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:26:49.364874Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa1b9427-e8b6-4f51-88fd-c7fb2fe21139 · inbound
SEAM: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models cites this paper.
SEAM: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Reference 117
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T16:32:43.442412Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4bd296a6-4d12-437d-8379-72d21ffec358 · inbound
OptiMat Alloys: a FAIR, living database of multi-principal element alloys enabled by a conversational agent cites this paper.
OptiMat Alloys: a FAIR, living database of multi-principal element alloys enabled by a conversational agent Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:41:29.457203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2a0acf3a-d9fd-4b34-b47e-a6c20e70208a · inbound
LARA: Validation-Driven Agentic Supercomputer Workflows for Atomistic Modeling cites this paper.
LARA: Validation-Driven Agentic Supercomputer Workflows for Atomistic Modeling Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T20:26:11.579754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b52b7a8b-7295-4aa9-8454-ec7109337d57 · inbound
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T17:31:07.439368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e70592b8-592e-4117-8f9d-06b821dcb821 · inbound
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines cites this paper.
From Text to Discovery: How Large Language Models Are Reshaping Research Across Scientific and Humanistic Disciplines Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:03:26.059957Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.