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Paper Citation Record · LEDGER

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search

As of 14 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 3 inbound Pith citation observations for arXiv:2506.08669.

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

pith.paper-citation-record.v1
2506.08669 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:10:39.603710Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T16:21:58.076991Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:57:30.323247Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 894f92e8-80af-4f83-9d1e-d44eb04c560e · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.466526Z digest=sha256:a23147f6c031a4e9fc3852635873a67065364211b373b1e607178875fdf86b4d

Observation 0ae34efb-0ceb-4a32-ac44-964a2b928fa9 · outbound

This paper cites PromptWizard: Task-Aware Prompt Optimization Framework.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search PromptWizard: Task-Aware Prompt Optimization Framework

Reference 2

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no resolver link, observed 2026-08-07T05:10:39.471820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.471820Z digest=sha256:e6f9cb3aa90669468342fe03573261e71ffc2bbbc752cea7a6a0b9f1a59f248e

Observation acdfeb69-f606-44fa-8a29-a5a3b8ae8ad1 · outbound

This paper cites Program Synthesis with Large Language Models.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Program Synthesis with Large Language Models

Reference 3

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no resolver link, observed 2026-08-07T05:10:39.476798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.476798Z digest=sha256:b5a14b78db3c553573ee5bc0c896e5268948d9bd324d1de6e73c6ff333152511

Observation beeb8d2b-5791-41e2-9814-c42e0dbfced2 · outbound

This paper cites Language Models are Few-Shot Learners.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Language Models are Few-Shot Learners

Reference 4

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no resolver link, observed 2026-08-07T05:10:39.483953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.483953Z digest=sha256:799842cc4f23f1281c591e0d18e1598730f7bb67e8af3fff89da7a2633253e69

Observation 1c3491ff-d83b-4fa8-bedb-46ca7315fec1 · outbound

This paper cites W., Sutton, C., Gehrmann, S., et al.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search W., Sutton, C., Gehrmann, S., et al

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.490703Z digest=sha256:5da4804ff0b065f24c1417c735683817a92d3dd282e45ba50f9b1aa68f3280f4

Observation 966d0ff8-ebcc-4caa-8c36-68cd24de5fd1 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Training Verifiers to Solve Math Word Problems

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.495670Z digest=sha256:04874029f4fd4d839c9532ff0d2bc8b3945fe10836cfbb906f3a55949fa2fd8f

Observation 1d8ed3ec-49bf-4b51-9ed1-26ae0b82aff0 · outbound

This paper cites RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.500635Z digest=sha256:02e6beb1091e69d08027462c907e09d9b35ddc3d2326f829840abf3386a9ff20

Observation 03471fb4-6d77-446f-84f9-d049ecde82ec · outbound

This paper cites M., Tong, S., Lepikhin, D., Xu, Y., Krikun, M., Zhou, Y., Yu, A.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search M., Tong, S., Lepikhin, D., Xu, Y., Krikun, M., Zhou, Y., Yu, A

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:39.861845Z

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.

source=arxiv_source observed=2026-08-07T05:10:39.505515Z digest=sha256:b41df15c5c3995b6f14301cb6532e1f2cb5bdc2bb0bf471736dacba7f2a7bfef

Observation 552b034e-9c43-41e5-8efe-3ddb14102fad · outbound

This paper cites Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution

Reference 9

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no resolver link, observed 2026-08-07T05:10:39.510387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.510387Z digest=sha256:7e09ab7c0af2111a58c65a901ef0e56d83ba6e0af2cbb93c106f558c03024162

Observation 47993681-8a81-44c5-8701-f389aa263739 · outbound

This paper cites Mistral 7B.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Mistral 7B

Reference 10

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.516361Z digest=sha256:77e728d84ca98c19d580012cfa169a091ca82faa1d27efb6a1241f3d35aca081

Observation 44ffee66-f1b0-409a-86e9-9ca8aacdc904 · outbound

This paper cites Crafting papers on machine learning.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Crafting papers on machine learning

Reference 11

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no resolver link, observed 2026-08-07T05:10:39.522382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.522382Z digest=sha256:7161ee69c93a28e99cae461f6efbcca766da81c8fad07162e598c08ebb06075e

Observation 47769cfe-a78e-4998-9b0f-55acd2329bae · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 12

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no resolver link, observed 2026-08-07T05:10:39.527540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.527540Z digest=sha256:39b17a18e9de901a10e8126c1f3bb719154835c995706604cdb91528dd712781

Observation 9d790766-19e5-4b81-a86f-18992f9ef9e3 · outbound

This paper cites Large Language Model Guided Tree-of-Thought.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Large Language Model Guided Tree-of-Thought

Reference 13

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no resolver link, observed 2026-08-07T05:10:39.532162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.532162Z digest=sha256:56218fe09e17b3444ae09f854f27cdd8e669b2b980ae4bcd623100d8598426aa

Observation 17c71aa8-be3f-4bb1-8258-d9a466ab742b · outbound

This paper cites Are Large Language Models Good Prompt Optimizers?.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Are Large Language Models Good Prompt Optimizers?

Reference 14

Resolution
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no resolver link, observed 2026-08-07T05:10:39.537689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.537689Z digest=sha256:6e9fda0543eb0274c4343ad74ca824eea262b9de6e03965b6771850704c57140

Observation 658038fb-0df3-4a0c-94ee-9ad55d451652 · outbound

This paper cites Teaching Small Language Models to Reason.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Teaching Small Language Models to Reason

Reference 15

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no resolver link, observed 2026-08-07T05:10:39.542301Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.542301Z digest=sha256:042c80c29cf17f691f24eef4f02199ea8da6e15ff798f5f6bdb90314cd427790

Observation 35e8c7bf-09fa-4ae6-a036-9701248b87c8 · outbound

This paper cites Hello gpt-4o.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Hello gpt-4o

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:39.843326Z

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.

source=arxiv_source observed=2026-08-07T05:10:39.547729Z digest=sha256:73821598e69d08bc38f9f89a042e597c3254b52d1efd8be66f01f21e9eb10667

Observation 886ca0ed-fe3a-44ae-908d-97d1d24cf0e1 · outbound

This paper cites Gpt-4o mini: Advancing cost-efficient intelligence.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Gpt-4o mini: Advancing cost-efficient intelligence

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:10:39.829705Z

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.

source=arxiv_source observed=2026-08-07T05:10:39.553899Z digest=sha256:386a04eeed79c8a17dd88e4086e0310d9c43c6af7e6de87a806f3cb1b450d567

Observation 9817da71-1d6d-4c95-bca6-6f241c3dd680 · outbound

This paper cites Automatic Prompt Optimization with "Gradient Descent" and Beam Search.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Reference 18

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no resolver link, observed 2026-08-07T05:10:39.559056Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.559056Z digest=sha256:56ece164148f95784596cc0a8252c03cfeeadd7e830772d67e528aed4872b123

Observation 589d0635-5f6a-4ccb-92ca-8ba541e8616a · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 19

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source=arxiv_source observed=2026-08-07T05:10:39.563785Z digest=sha256:ba3f23ddb152825a04bd66306836ffaa6e3d0b6a810300abf7e5c36190e95413

Observation 17a2411b-9c09-491b-81e1-c191ed6b30d3 · outbound

This paper cites Efficient Large Language Models: A Survey.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Efficient Large Language Models: A Survey

Reference 20

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source=arxiv_source observed=2026-08-07T05:10:39.570052Z digest=sha256:0163aa1bbd8fd7dfd30d1cefb9b774655cfb7268990893d971eba8d424403b6a

Observation 639404a0-88ce-4b85-92d0-bed2a024a3a4 · outbound

This paper cites V., Zhou, D., et al.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search V., Zhou, D., et al

Reference 21

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no resolver link, observed 2026-08-07T05:10:39.575658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.575658Z digest=sha256:98c9dc89554f3e3c12dd1e5f3a677a7e980d45a0ceed68fdfb9a34efce77cd9a

Observation fd5eb637-3f5e-40c1-a072-fe4f88997273 · outbound

This paper cites Larger language models do in-context learning differently.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Larger language models do in-context learning differently

Reference 22

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no resolver link, observed 2026-08-07T05:10:39.580010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.580010Z digest=sha256:b3af5ac1a6018cf5cac55d27b0dc21f9c54a1f447ec0925ad2dbb8112766ad69

Observation 26a8e1bd-7d69-4e0d-9ba2-5d5168bc7efb · outbound

This paper cites Zhongjing: Enhancing the chinese medical capabilities of large language model through expert feedback and real-world multi-turn dialogue.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Zhongjing: Enhancing the chinese medical capabilities of large language model through expert feedback and real-world multi-turn dialogue

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-07T05:10:39.811024Z

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.

source=arxiv_source observed=2026-08-07T05:10:39.586434Z digest=sha256:58b6cacfd33a99c8bc0a0486651c0c1a3f491adb70aaef91a91112c72eda01bc

Observation 07d6517c-d09c-4578-a9f8-c6fbaa0ad8f1 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search ReAct: Synergizing Reasoning and Acting in Language Models

Reference 24

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no resolver link, observed 2026-08-07T05:10:39.593295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.593295Z digest=sha256:ee4a4e89cac49ed8a75f0ee004aa42e3b914a00ff29185ff0e73598d66c3d8e4

Observation 6615a069-eded-4c64-8a39-bf32737c3ec4 · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search Large Language Models Are Human-Level Prompt Engineers

Reference 25

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.599290Z digest=sha256:675158e9aee63367ad4321c3a691d5076feba1925d6aecfb3cfe76a90009cf7b

Observation c922c6e6-575a-4a07-826a-3e763703ee40 · outbound

This paper cites write newline.

Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search write newline

Reference 26

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no resolver link, observed 2026-08-07T05:10:39.603710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:10:39.603710Z digest=sha256:0ffd8e710b524fb3c71fdf987b13c6d6134d14cbbccb8aaadf738687851fe93a

Pith citing papers

Observation 4b6429ff-78c4-4dad-b48d-be30648211ef · inbound

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models cites this paper.

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search

Reference 235

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:40:41.453655Z

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.

source=pdf_text observed=2026-05-12T08:40:40.910461Z digest=sha256:76719e8b6dde5be85c1661321159c6cdcb3796e08ed04658e25e0bd32725ab45

Observation c7b9731c-c43d-4fd1-a02d-add407ee5e21 · inbound

SEF-CLGC at SemEval-2026 Task 11: Logical Notation Impact on Language Model Performance cites this paper.

SEF-CLGC at SemEval-2026 Task 11: Logical Notation Impact on Language Model Performance Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search

Reference 7

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metadata mismatch
arxiv_id, observed 2026-07-03T00:57:30.325259Z

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.

source=arxiv_source observed=2026-06-27T16:53:44.256573Z digest=sha256:94044e550e5766998ffa83df8773d4680eab26ea827d583ce1ed880ff63b74b1

Observation 4a7c5f08-f794-4fc0-9883-da6087dda01b · inbound

AdaHome: An Adaptive Smart Home Assistant using Local Small Language Models cites this paper.

AdaHome: An Adaptive Smart Home Assistant using Local Small Language Models Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search

Reference 4

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unresolved
no resolver link, observed 2026-08-01T16:21:58.076991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T16:21:58.076991Z digest=sha256:b34d5aec52e52636573ab8af6a1985bffa8285df7dae92a86cb3f763cbf9a876