Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:39:28.914843Z
Paper Citation Record · LEDGER
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering
As of 14 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2501.04277.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:39:28.828160Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T21:39:29.104024Z
Reference resolution
16 of 16 outbound references displayed
- verified exact1
- verified fuzzy3
- unresolved10
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 8afefc89-0258-4b22-880a-7376396eccf0 · outbound
This paper cites an unresolved cited work.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T21:39:29.230362Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c0a4eb22-a3f7-4d60-a8f2-c3fa0d82aac3 · outbound
This paper cites Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-10T21:39:29.109331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 202f8f99-9b0b-4d6e-b06e-5f67a63b59f0 · outbound
This paper cites as shown in Figure 4 a) and then submitted the question in the format:.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering as shown in Figure 4 a) and then submitted the question in the format:
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:39:29.212989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 587d145e-9ce5-464e-b9a6-fea7db280648 · outbound
This paper cites DARWIN Series: Domain Specific Large Language Models for Natural Science.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering DARWIN Series: Domain Specific Large Language Models for Natural Science
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.876342Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 65facf27-8e31-4336-bf23-7d24820ac903 · outbound
This paper cites LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.882140Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33188d1a-c76c-4c1d-b123-cadd1ba158ab · outbound
This paper cites MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering MatSci-NLP: Evaluating Scientific Language Models on Materials Science Language Tasks Using Text-to-Schema Modeling
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.887635Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 266c0686-ccd8-4052-8662-a330b59f8567 · outbound
This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Measuring Mathematical Problem Solving With the MATH Dataset
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.893097Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e47cab3-0f05-4dde-a894-de1dcf75ee87 · outbound
This paper cites MCQ tasks, while simpler, can be impacted by pattern exploitation where models rely on super- ficial cues rather than true conceptual understanding.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering MCQ tasks, while simpler, can be impacted by pattern exploitation where models rely on super- ficial cues rather than true conceptual understanding
Reference 14
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-10T21:39:29.194247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c419435c-7750-44c0-a438-719a0d9faebd · outbound
This paper cites Brugger, S.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Brugger, S
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:39:29.161125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation bf27e63c-6dad-442f-9f6a-cfc27c40b819 · outbound
This paper cites an unresolved cited work.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T21:39:29.143942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation ef65b4e2-16d8-4e3d-b14b-911b91249f19 · outbound
This paper cites an unresolved cited work.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T21:39:29.126027Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation cbf31625-cd31-4f16-90e6-24924600d375 · outbound
This paper cites Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities
Reference 327
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.852629Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3950b9dd-9eae-4880-823f-764127d3ec7f · outbound
This paper cites Mixtral of Experts.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Mixtral of Experts
Reference 2015
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.899040Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c1eb0834-1fcc-41d5-9569-50ea4b697727 · outbound
This paper cites Knowledge Graph Question Answering for Materials Science (KGQA4MAT): Developing Natural Language Interface for Metal-Organic Frameworks Knowledge Graph (MOF-KG) Using LLM.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Knowledge Graph Question Answering for Materials Science (KGQA4MAT): Developing Natural Language Interface for Metal-Organic Frameworks Knowledge Graph (MOF-KG) Using LLM
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:39:28.858082Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d494446-e88a-444a-90a5-3797306c65b0 · outbound
This paper cites Welbl, N.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Welbl, N
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:39:29.177058Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e1e28461-e30d-4423-afe1-c2748fb5d8d0 · outbound
This paper cites MoleculeQA: A Dataset to Evaluate Factual Accuracy in Molecular Comprehension.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering MoleculeQA: A Dataset to Evaluate Factual Accuracy in Molecular Comprehension
Reference 2024
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T21:39:29.051729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Pith citing papers
Observation c0a4eb22-a3f7-4d60-a8f2-c3fa0d82aac3 · inbound
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering cites this paper.
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering
Reference 2
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-10T21:39:29.109331Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.