Paper Citation Record · LEDGER

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 5 inbound Pith citation observations for arXiv:2412.14454.

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

pith.paper-citation-record.v1
2412.14454 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:18:03.137960Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:27:44.516169Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T18:42:29.071864Z

Reference resolution

38 of 38 outbound references displayed

verified exact0
verified fuzzy23
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2c93bb04-cca1-4653-87b9-a10d4772ef6b · outbound

This paper cites In: RecSys.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: RecSys

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.815109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2198808e-f0d0-4f03-96f3-cb384da1aa49 · outbound

This paper cites In: RecSys.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: RecSys

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.796593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a63ea409-e4d3-41f3-8c41-5bd5bf88194e · outbound

This paper cites an unresolved cited work.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:18:03.781912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3af0a5ac-9a6c-4628-9d11-b93da1f44f3d · outbound

This paper cites an unresolved cited work.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:18:03.765958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bfbf8479-e11a-4a0e-a002-ea9dd68c46d7 · outbound

This paper cites In: NAACL-HLT (1).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: NAACL-HLT (1)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.749667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6b9afcb4-1d3d-4840-8309-118177252e93 · outbound

This paper cites Evaluating ChatGPT as a Recommender System: A Rigorous Approach.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Evaluating ChatGPT as a Recommender System: A Rigorous Approach

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:02.984741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acaef430-36c5-485c-b48d-ce383165937e · outbound

This paper cites TKDE01, 1–20 (5555).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems TKDE01, 1–20 (5555)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.733162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 32476ef6-1838-4a74-99a1-04b20a09317a · outbound

This paper cites In: EMNLP (1).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: EMNLP (1)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.716178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation be228c98-2902-4e8e-ac5d-802a95058c81 · outbound

This paper cites In: CIKM.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: CIKM

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.700415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4f7e6387-c041-43a6-aaf7-995183fb51e0 · outbound

This paper cites In: ECIR (2).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: ECIR (2)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.685078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ac9eb7d8-087f-4b88-8fdc-e38882309a7c · outbound

This paper cites In: ECIR (3).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: ECIR (3)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.668469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 91d98798-337b-4c7e-ac20-b6c486fd3af1 · outbound

This paper cites ACM Comput.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems ACM Comput

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.651641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation be49ec38-a664-467f-901e-40e0cfd7d526 · outbound

This paper cites Computer42(8), 30–37 (2009).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Computer42(8), 30–37 (2009)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.635159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c19760c-81c6-41fb-8e65-7b6d7984d5a8 · outbound

This paper cites In: LREC/COLING.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: LREC/COLING

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.616875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1ea71f95-b1d8-4eaa-b7ee-29b76b0e58cd · outbound

This paper cites ACM Trans.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems ACM Trans

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.596171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0758fc2b-fba1-477b-b8df-5ad2263f9833 · outbound

This paper cites an unresolved cited work.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:18:03.580961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0a410071-dd75-48a4-85b7-da6d9da60ca4 · outbound

This paper cites an unresolved cited work.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:18:03.566280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d6b49182-ac73-4108-b215-b8922226126c · outbound

This paper cites Is ChatGPT a Good Recommender? A Preliminary Study.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Is ChatGPT a Good Recommender? A Preliminary Study

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.039725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63ad0620-91c5-42df-aceb-3f901cf027db · outbound

This paper cites In: EMNLP/IJCNLP (1).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: EMNLP/IJCNLP (1)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.550163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9448fafc-eeb3-4bf3-bb30-2ca91ffa438a · outbound

This paper cites In: NAACL-HLT.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: NAACL-HLT

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.535427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 23509f47-d63b-4141-94bc-d86de0cacd57 · outbound

This paper cites org/CorpusID:160025533.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems org/CorpusID:160025533

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.519810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a7a7b397-8210-4878-bc8e-3fc0e95b0d81 · outbound

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

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.059957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e35e703b-228d-48e0-a112-4a3052a87e60 · outbound

This paper cites In: RecSys.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: RecSys

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.502940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eae16346-f381-4042-ba9d-d4dda41d8091 · outbound

This paper cites One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.069922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cf4d69e-0e06-472f-9513-0638ea37d6cc · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems LLaMA: Open and Efficient Foundation Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.075010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb5c8579-8059-44c0-9f5a-63aed889bcd7 · outbound

This paper cites A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.079647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb64c172-14b3-41e1-a648-49a2a40e54c9 · outbound

This paper cites In: NeurIPS.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: NeurIPS

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.485989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bfb4c971-3af4-44e5-b29d-d2329add035f · outbound

This paper cites In: WWW (Companion Volume).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: WWW (Companion Volume)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.469074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9a8791ec-b6a4-4870-a9d9-9a5dc0fe4cb5 · outbound

This paper cites Zero-Shot Next-Item Recommendation using Large Pretrained Language Models.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Zero-Shot Next-Item Recommendation using Large Pretrained Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.093292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0787f53d-ae4e-4376-9e36-44d7bc3e2144 · outbound

This paper cites In: NAACL-HLT.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: NAACL-HLT

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.449640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f6494cc2-90e0-4284-8322-441b058f9381 · outbound

This paper cites In: NAACL-HLT.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: NAACL-HLT

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.431895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3f10669e-35fc-4d14-b5af-712f743758a7 · outbound

This paper cites In: ACM Multimedia.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: ACM Multimedia

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.411279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a4d8e1da-d564-403b-8942-f5f90eedb6ea · outbound

This paper cites World Wide Web (WWW)27(5), 60 (2024).

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems World Wide Web (WWW)27(5), 60 (2024)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.396066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f977c16b-ac1c-46b4-ae4b-5349d7de2b95 · outbound

This paper cites an unresolved cited work.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:18:03.380123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 04a2ff19-0ffc-4316-9275-81cecc572350 · outbound

This paper cites Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.122200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dc43ab7-afff-40db-ade2-e6d76beccbb9 · outbound

This paper cites LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:03.127522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52643386-a20f-4cd2-9020-01b3ef727f3c · outbound

This paper cites an unresolved cited work.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:18:03.364114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6b89139f-192d-43c9-b4cc-f236cf42afcf · outbound

This paper cites In: WSDM.

Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems In: WSDM

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:18:03.348343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 96a8f860-89cf-450a-8125-f2f81fccd38f · inbound

AutoData: A Multi-Agent System for Open Web Data Collection cites this paper.

AutoData: A Multi-Agent System for Open Web Data Collection Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T15:27:44.516169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 073b46af-19c6-4efd-b97c-a8f5e8cf3719 · inbound

Fine-tuning on simulated data outperforms prompting for agent tone of voice cites this paper.

Fine-tuning on simulated data outperforms prompting for agent tone of voice Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T19:42:01.551848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8179a10f-1b05-4d8d-a1ce-be14d28f1773 · inbound

CTG-Insight: A Multi-Agent Interpretable LLM Framework for Cardiotocography Analysis and Classification cites this paper.

CTG-Insight: A Multi-Agent Interpretable LLM Framework for Cardiotocography Analysis and Classification Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T12:01:23.434340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdfeb420-9850-486b-85f9-2856966438ab · inbound

Unravelling the Probabilistic Forest: Arbitrage in Prediction Markets cites this paper.

Unravelling the Probabilistic Forest: Arbitrage in Prediction Markets Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T04:27:42.136860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9094fa3-5973-44ba-8609-e1761bc10aa5 · inbound

Trustworthy Recommendation in the Era of Large Language Models: Opportunities and Challenges cites this paper.

Trustworthy Recommendation in the Era of Large Language Models: Opportunities and Challenges Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systems

Reference 109

Resolution: verified exact; arxiv_id, observed 2026-06-28T18:42:29.073311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.