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Paper Citation Record · LEDGER

LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2401.17244.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2401.17244 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:06:30.878197Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T00:30:49.318289Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 23acfc3e-87c5-4d32-9e2f-3cc662d92a77 · inbound

MDCrow: Automating Molecular Dynamics Workflows with Large Language Models cites this paper.

MDCrow: Automating Molecular Dynamics Workflows with Large Language Models LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T21:06:30.878197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:06:30.878197Z digest=sha256:e2dc5a78510437a84e6f92d0a8c1ea3b9e21eea34289e3c93ee61ce37140ce5e

Observation e9b0dfb2-a01e-4b78-a5d5-c18e58551f5a · inbound

AutoChemSchematic AI: Agentic Physics-Aware Automation for Chemical Manufacturing Scale-Up cites this paper.

AutoChemSchematic AI: Agentic Physics-Aware Automation for Chemical Manufacturing Scale-Up LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:26.372367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:26.372367Z digest=sha256:e42b4d856feda2f5a738072a79480932ef15d9d57e158690b03efc2ddec45202

Observation 9f520be4-78d4-4a38-8a2c-741941d881ed · inbound

HPC-AI Coupling Methodology for Scientific Applications cites this paper.

HPC-AI Coupling Methodology for Scientific Applications LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T00:23:47.060277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:23:47.060277Z digest=sha256:9a0197ae46e7601c35e5eea874b23ad36f587fcdafc19204cb454b2525226ab5

Observation d8745fa3-c63e-4fb5-b627-6f9ff7ce36c8 · inbound

Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design cites this paper.

Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-22T00:30:49.321205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T00:26:35.977160Z digest=sha256:42bba3de3a52dca0de462934aa6cd8519915504bc42ad51e5153a573b649857a

Observation 0cf64225-bdd0-4e2b-aeb3-454ee3f5ce53 · inbound

Spotlighter: Revisiting Prompt Tuning from a Representative Mining View cites this paper.

Spotlighter: Revisiting Prompt Tuning from a Representative Mining View LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-05T13:10:08.197899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:10:08.197899Z digest=sha256:368f561d9988d41c14e4358f7e95f2de1cf553ff7bd47683e3387fccb9b84559

Observation 7da8d219-46fe-463f-9bc9-cb82136506e8 · inbound

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory cites this paper.

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 293

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T23:13:16.039742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-14T23:13:15.016486Z digest=sha256:a1e9b293d247a0b0db60e3854ba4eb985ac6c4e231aa8e32611b794fb3d7c36d

Observation 2578bf27-a7dc-44f1-9e46-b7ec8a1f391d · inbound

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org cites this paper.

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-03T16:56:21.035093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:56:21.035093Z digest=sha256:492af2778e5ab2fc5fc33d11dd364c964d33172c7820b32d5e16e14ae59d77e0

Observation 3a12976a-9d46-4f6b-bac2-9ff522b9893d · inbound

El Agente Quntur: A research collaborator agent for quantum chemistry cites this paper.

El Agente Quntur: A research collaborator agent for quantum chemistry LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-16T06:50:42.503877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T06:48:44.713745Z digest=sha256:db7e49043279caaf26efcc508b35167ce0c112df2374c092955815a0feb9b358

Observation 4dd91cf4-2a55-447f-8998-90fbdc36ca0b · 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 LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:41:30.468465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T21:14:23.125924Z digest=sha256:8127d62500d6c98a1cc614300772524e35d6b92492e8223ab646d198f23dc884

Observation b4d95a23-a141-4bbc-bf61-de789405d406 · inbound

GRAIL: A Deep-Granularity Hybrid Resonance Framework for Real-Time Agent Discovery via SLM-Enhanced Indexing cites this paper.

GRAIL: A Deep-Granularity Hybrid Resonance Framework for Real-Time Agent Discovery via SLM-Enhanced Indexing LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:25:40.811334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T18:29:32.989360Z digest=sha256:3d5cdd478198520d9ea92420ee6ab848ee4af12164e8893e6ed589875569a378

Observation 810acc36-223a-402d-9947-90aaf976c81e · inbound

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry cites this paper.

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation

Reference 271

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:21:10.505347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T17:38:30.092429Z digest=sha256:f334742250e16b30a80f5cdde9befc5649ff69bdc6370e77fdb47d671371182a