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Paper Citation Record · LEDGER

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education

As of 22 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 2 inbound Pith citation observations for arXiv:2412.15902.

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

pith.paper-citation-record.v1
2412.15902 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:03:24.573807Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T17:38:19.304425Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff01f038-6f5f-4d8f-a795-d3b2e0fd3b2c · outbound

This paper cites Can Large Language Models perform Relation-based Argument Mining?.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Can Large Language Models perform Relation-based Argument Mining?

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.273411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.273411Z digest=sha256:ff3d7a3c7a1feecd33f4e02fc7abe904a9759dfe3fb499fc87c976e77f56f03a

Observation 141df9cd-9b31-47bf-a3d1-aef64d50f739 · outbound

This paper cites Large Language Models in Law: A Survey.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Large Language Models in Law: A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.322041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.322041Z digest=sha256:a8a8ac331a49bbece79c47cd1ceea82ebee03496f399540850872822c5e2c9cb

Observation 1ba9c8b7-393a-405c-a5e0-718b7c687ff7 · outbound

This paper cites Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.326637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.326637Z digest=sha256:9d26cdea7929c0ae2d8efb441da16755c99129e5a2f59c9b1a9bdda16101a244

Observation ddfa37b6-e318-4599-a3b0-53b8b479e4ce · outbound

This paper cites an unresolved cited work.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-11T11:03:24.915387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T11:03:24.336305Z digest=sha256:4ee88455d190a267ec14782230ac6e8e65393638d99dee36f1b96471a3cab04e

Observation 1d9460fb-0eb0-43c4-9f02-87bcc3cdfd20 · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.344552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.344552Z digest=sha256:bcaefafab8b56b1dfd0c4d6c328ce94b3820f2ba6d7b0a99e47e1b08e75772d3

Observation 427bfb74-59d8-4b6a-8c38-a5a13b551b8f · outbound

This paper cites Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.404105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.404105Z digest=sha256:0d3b8a75b7b5d0116dfb49d08951ce9d710bce9173d84c47e5552099cc7d28c5

Observation 3bd9a36f-9761-4138-a4d6-a24f1495f9d5 · outbound

This paper cites InFindings of the Association for Com- putational Linguistics: ACL 2023, pages 2296–.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education InFindings of the Association for Com- putational Linguistics: ACL 2023, pages 2296–

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:03:24.828046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T11:03:24.508095Z digest=sha256:f3a360e8b671e364200a6a4f2b2eb6961a9851c2b508305144defb8865476b51

Observation 3a667fa7-d5d6-4306-b62b-9c9678e95df6 · outbound

This paper cites Human-AI Collaborative Essay Scoring: A Dual-Process Framework with LLMs.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Human-AI Collaborative Essay Scoring: A Dual-Process Framework with LLMs

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.554885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.554885Z digest=sha256:f9fb7b4a1e91b9949b08a395b676446c9ead4a1012925367b8c194daea657ed8

Observation ca9b6738-d936-440c-a76a-69343249a44b · outbound

This paper cites InFind- ings of the Association for Computational Lin- guistics: EMNLP 2020, pages 1560–1569.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education InFind- ings of the Association for Computational Lin- guistics: EMNLP 2020, pages 1560–1569

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:03:24.798341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T11:03:24.568911Z digest=sha256:8172f2bf35a7a75b6fbffacea5c68eab6127d7df5c3ecf38728074ab54fdfa2a

Observation ccd4547b-c489-4a05-b4dc-a032f1dd5e70 · outbound

This paper cites In Proceedings of the 2016 conference on empirical methods in natural language processing, pages 1882–1891.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education In Proceedings of the 2016 conference on empirical methods in natural language processing, pages 1882–1891

Reference 2016

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:03:24.840550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T11:03:24.461620Z digest=sha256:9b9325a6ef6a9ea1754254770ee4c0014a3068ed2c66b2dd23aaa96bee8d9c73

Observation 3fec82fc-fdb3-4dac-88fa-155a6efc4c16 · outbound

This paper cites Language models and Automated Essay Scoring.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Language models and Automated Essay Scoring

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.340477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.340477Z digest=sha256:d403fdac517daffca4638577705edcf5dd2426676ccba8e9549f860847523a2e

Observation f024f1d7-a5e4-47a3-8522-54c723970a42 · outbound

This paper cites Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, Dominic Culver, Rui Melo, Caio Corro, Andre FT Martins, Fabrizio Esposito, Vera Lú- cia Raposo, Sofia Morgado, et al.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, Dominic Culver, Rui Melo, Caio Corro, Andre FT Martins, Fabrizio Esposito, Vera Lú- cia Raposo, Sofia Morgado, et al

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:03:25.093120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T11:03:24.181365Z digest=sha256:b7ce0fba23fd7ebb6511b96b16ccaaf90cf1b5b7f0ccc05fcc8dad6dd756eff6

Observation 5b2513b3-a4e3-490b-8421-0e4f59395eee · outbound

This paper cites Automated essay scoring using efficient transformer-based language models.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Automated essay scoring using efficient transformer-based language models

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.331318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.331318Z digest=sha256:ec590538acb1c2c16adb89a903dd8d41460cc9768bd2959e47b66f733c821072

Observation 296a3079-1ce5-4580-b39d-29b648331e51 · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education Automatic Chain of Thought Prompting in Large Language Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.573807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.573807Z digest=sha256:d6b75060bad11a6e9900d352db0a0c0ffe96830842d6634bd38dd9d380b251f6

Observation cc95d7c0-4b50-4693-b080-82887a012995 · outbound

This paper cites GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.119470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.119470Z digest=sha256:ebacda662c7cbd67a540583889c51f7526cce3da17e17e1ce3a83a0d82a2d270

Observation 7aacdcd7-747b-445a-90cb-2c43e65323d6 · outbound

This paper cites SaulLM-7B: A pioneering Large Language Model for Law.

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education SaulLM-7B: A pioneering Large Language Model for Law

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-11T11:03:24.230295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:03:24.230295Z digest=sha256:656d02d4f1b871a2dc39bc1f31897e8754a88c7d1b6f0960424130e237742186

Pith citing papers

Observation a22e5db3-f006-43bd-9a50-adcc13975fda · inbound

GradeLegal: Automated Grading for German Legal Cases cites this paper.

GradeLegal: Automated Grading for German Legal Cases On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:09:38.524511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-21T05:06:33.678046Z digest=sha256:26521a6a4c2bbfa855fcd60dac01c667db9af3403a1bdcdba1273198838bda20

Observation 72de590b-ad5e-40d5-a53e-db11c5a3ef97 · inbound

PsyScore: A Psychometrically-Aware Framework for Trait-Adaptive Essay Scoring and ZPD-Scaffolded Feedback cites this paper.

PsyScore: A Psychometrically-Aware Framework for Trait-Adaptive Essay Scoring and ZPD-Scaffolded Feedback On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-06-26T17:39:40.215346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-26T17:38:19.304425Z digest=sha256:9bc2ed94e613de149337cbbcb0e4141554ac15b194c3a1832199a50bc22a8649