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Paper Citation Record · LEDGER

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval

As of 13 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 2 inbound Pith citation observations for arXiv:2411.16454.

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

pith.paper-citation-record.v1
2411.16454 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:09:39.909360Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T06:30:55.592334Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T15:28:33.903435Z

Reference resolution

50 of 50 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved46
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f1b6429-e353-439e-b375-bc81452eb73e · outbound

This paper cites online" 'onlinestring :=.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval online" 'onlinestring :=

Reference 1

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unresolved
no resolver link, observed 2026-08-12T13:09:39.638868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.638868Z digest=sha256:13ec3809ae585a73cc68074559b290199a7876e3176f1a001a9fc409bc58564d

Observation 958da3e2-2177-47b7-9d77-1b22065507dd · outbound

This paper cites write newline.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.645223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.645223Z digest=sha256:23e28ce8e30f9cbe18b3d96d6ecce9cdad8748e9e1bc0e1deeeaea09092f0f3a

Observation 0d95168c-04bc-40ab-bc3f-a206efc77f2e · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.748736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.656073Z digest=sha256:7bd82ad6c43ad12ac6492652fc96af5e8f05c60b996eb6f85982089f7cb30166

Observation ddc44951-eceb-442a-9870-e92b0b93c2df · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 5

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unresolved
no resolver link, observed 2026-08-12T13:09:39.661315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.661315Z digest=sha256:2fb2f0f801ebd46ddef38dcc894407bb78b56476bdbda1b0246df86f184fb9c9

Observation ccd6193a-75f3-4f86-a0f8-8aecd1956542 · outbound

This paper cites Cause and Effect: Can Large Language Models Truly Understand Causality?.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Cause and Effect: Can Large Language Models Truly Understand Causality?

Reference 6

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unresolved
no resolver link, observed 2026-08-12T13:09:39.666961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.666961Z digest=sha256:5a4959b80aeb9273fb663e158ac6cb36f564c40578be77e5e910bbee40be925c

Observation 210f46b6-c1e4-4392-b57b-847c68d8386b · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.672423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.672423Z digest=sha256:d7181bedba8f450da49e763804a2bb7f99c8af7ec15d6d71d7073b94f07613bf

Observation b452ce00-8f68-4219-beb0-5aad4150a282 · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval A Simple Framework for Contrastive Learning of Visual Representations

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.678281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.678281Z digest=sha256:76d9b4c182248a304b77ffb51943d3c6c8174251896d91b30fef0f486c5a75ac

Observation b36fdda9-6bdd-438f-8b8f-b41b437e7c2e · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.718756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.684963Z digest=sha256:d6c017d0faa8238e11f1fa457a13583f1d60334cb4609476eafe1d8b19e75ab0

Observation 228bddac-d541-4c49-81c3-5f832188b89c · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Training Verifiers to Solve Math Word Problems

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.690215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.690215Z digest=sha256:0f4690bc6c10778c47cfe87f8ceb467b2cef6d22a03f5de17b5c864de6bcbb12

Observation d91d596b-d329-4400-9c51-a1a9fd220be8 · outbound

This paper cites SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented Generation

Reference 11

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unresolved
no resolver link, observed 2026-08-12T13:09:39.697063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.697063Z digest=sha256:214757c418b583fb498b625a82dec4951bd15bed12e87c7ce71abd5c9483521f

Observation 7921a2b4-ceec-4a8b-8e97-d57e929dffbc · outbound

This paper cites The Llama 3 Herd of Models.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval The Llama 3 Herd of Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.703415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.703415Z digest=sha256:e39d547913d1113b38a48746422264feb6205a60e23459ad90ca4448e2873fa3

Observation b668ad30-1128-4d90-969e-8167e8bfbf0f · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.708768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.708768Z digest=sha256:59868c4619186367933e3bc328afe36f8cdabc01a68ed4b4dfc4e3b554ad739e

Observation f071bf18-c168-4bf3-8cf0-dae324f402aa · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.714386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.714386Z digest=sha256:6a872b2f27ecfe02e602f57a2ce26bdd94207b8ff43ea9a5084ce96bf9f71577

Observation 732fa33a-8e62-4173-b1a3-40ee1e08a7d0 · outbound

This paper cites Large Language Models Are Not Strong Abstract Reasoners.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Large Language Models Are Not Strong Abstract Reasoners

Reference 15

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unresolved
no resolver link, observed 2026-08-12T13:09:39.719843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.719843Z digest=sha256:93bae064161204cab68edf05dc1580097fe292b73bb2e34b3b7d6ca6bceb69f8

Observation 13bcac20-ebd8-4d2e-9415-8dd7fb7d36e9 · outbound

This paper cites Can Large Language Models Reason? A Characterization via 3-SAT.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Can Large Language Models Reason? A Characterization via 3-SAT

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.725102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.725102Z digest=sha256:7ba23221383232617788293fa40e5e400df878dd0fb08091b977f5f2830b13f8

Observation 28d02d17-ad07-4c25-92fb-7764cd372cbe · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.729948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.729948Z digest=sha256:8dd80d21b880dda5ec901ede191caf777bb3f404226d6bdf2077b0dac18abd88

Observation 5a242bf0-a22c-4e7d-9d0c-904898e4aa6d · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.676642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.734160Z digest=sha256:2634d42f71381966a7cb8a783a08320fea25b9fe6aa24f7836dc3fa2daa9798c

Observation 51dfa03d-e078-4495-9cad-34351a704229 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.656642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.739270Z digest=sha256:77539a75467d227b7a6fb91de16b40d1b94177cd39df5409a34b50442c7d8e24

Observation ee0f0ce0-5abf-4979-a898-3b663a2bd2da · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 20

Resolution
verified exact
doi, observed 2026-08-12T13:09:39.975610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.743712Z digest=sha256:d2504211ee6e0caaa26a519fbde7ef1b81ead5dea90369173cd1ebbfc3859197

Observation 5fe443e5-fd69-4b07-b1e6-6bae259a6291 · outbound

This paper cites Mistral 7B.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Mistral 7B

Reference 21

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unresolved
no resolver link, observed 2026-08-12T13:09:39.748848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.748848Z digest=sha256:4e2bbf7dbfb9364a098696249828ab63fa967cc6db408bbb3f42f598b674f9a9

Observation 88b586b7-c3e4-4ecc-a02e-128332885c4f · outbound

This paper cites Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems

Reference 22

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unresolved
no resolver link, observed 2026-08-12T13:09:39.753929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.753929Z digest=sha256:8472bc93db26624b30f175222b9387221ec6e35ff6b2dcf360b7ea4e92a5eff8

Observation f8d34b45-aecb-4a76-8dfc-6f9286bfeda6 · outbound

This paper cites BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.759451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.759451Z digest=sha256:0da03f78367391a99a57594278d9d78cac6919d6fb06c355ac27cc49f23943c9

Observation 58748d41-510d-40af-88f8-b8c3f5c03e5a · outbound

This paper cites u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.764315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.764315Z digest=sha256:f529ad5b4bcfbd5b47d989fb9aceaa7981e8e946ff33a277af3aa2b3415fde62

Observation c7f18baa-ff25-4c87-9719-632f8888d8c2 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.769164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.769164Z digest=sha256:db9f056b38fc2b17e77272599138778fa2b780bd98c467bcfb3a28d95afba5dc

Observation b9270f94-5786-4eb8-8153-1b205a201de4 · outbound

This paper cites GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval GT2Vec: Large Language Models as Multi-Modal Encoders for Text and Graph-Structured Data

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.774118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.774118Z digest=sha256:087ecfd4994c261b736a1f5925c13229f2c21fd0ec9be1bef8286dcfe920c23e

Observation 2e6776eb-de35-47e4-94bd-7e63f259cc4e · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.626711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.780735Z digest=sha256:f374559cc41455e0111d835bdedca2e143fb58abff1649d83c6f0f8be74c18b7

Observation d6abba34-273f-45ff-bc76-a2bf5518609a · outbound

This paper cites Pisces: A cross-modal contrastive learning approach to synergistic drug combination prediction.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Pisces: A cross-modal contrastive learning approach to synergistic drug combination prediction

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:09:40.610284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.785623Z digest=sha256:bea60996a56419d27beb884497db78c70f091a252b4200c4db7e7d5ffaf7827a

Observation 8e94fc62-c0ff-42c9-afc1-c432ea431a51 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.591526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.790592Z digest=sha256:7447032744bc34aa928a0295d0d8a3bab421f9bf76002dfe435e2a91b38b15de

Observation 5878ec42-4de5-49d7-a1e7-3c4143efe8b4 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.795879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.795879Z digest=sha256:201fa7906dd707c934b8b3e787cf84aa71d63410082f3d6e03c0121793f7e2ae

Observation c1539e70-40c7-454a-a8a1-52cf1d6e278f · outbound

This paper cites Decoupled Weight Decay Regularization.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Decoupled Weight Decay Regularization

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.800164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.800164Z digest=sha256:768c653d7a692559254a07850bbb6c7083257ad5545219e651d62f7078d6724a

Observation b773bd58-7d83-4c77-acd1-023100d3b2d3 · outbound

This paper cites Enhancing LLM Intelligence with ARM-RAG: Auxiliary Rationale Memory for Retrieval Augmented Generation.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Enhancing LLM Intelligence with ARM-RAG: Auxiliary Rationale Memory for Retrieval Augmented Generation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.804827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6913fd3d-4ec4-4df5-8ce4-6db1f6152e12 · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.810224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.810224Z digest=sha256:0b534656939c7ce20ab54794561c36ead57757292327301efb4834171994f409

Observation 0e5fe0b4-983a-4789-9676-7089f3e335dc · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Representation Learning with Contrastive Predictive Coding

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.816128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.816128Z digest=sha256:1c1e3b35f01d7c056b67cdb068b03ffc74c44d9e06478e86d32a4697757eae49

Observation b9049e04-efcf-4c35-9951-1435705dd373 · outbound

This paper cites GPT-4 Technical Report.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval GPT-4 Technical Report

Reference 35

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unresolved
no resolver link, observed 2026-08-12T13:09:39.821749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.821749Z digest=sha256:9c11a5e4a67d79af4810eae54cb53e966a9c7984728ba93ebc8227ff319a17b1

Observation de5fc493-f721-46da-996c-5b440615da6d · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.562504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.827588Z digest=sha256:9035ef45df980461e797c27cedfcc70a3f56773c828ef9403fa990c4df7f077d

Observation d6b0c734-0990-4c35-b4d5-035e86d4bac6 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.832886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.832886Z digest=sha256:c92325d3c5f6d1cc958047f754bb004c60b806b674080683bd7523ee8d91add1

Observation cd8ea612-04f4-4732-aba1-041fb7d7fb68 · outbound

This paper cites Openmathinstruct-2: Accelerating ai for math with massive open-source instruction data.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Openmathinstruct-2: Accelerating ai for math with massive open-source instruction data

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:09:40.532109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.837767Z digest=sha256:9ac3513309d3000148f38280c822201b95097842bedde71b7ddad32dd75d4a94

Observation f1dc75d5-7ef1-473c-beca-7a1687814d0c · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.843014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.843014Z digest=sha256:ac32023079bc80ed21ea8e03c9a9ae5f6d05d4e565fe230f5ee47fe4ab719f83

Observation d7dcd36a-d4a7-4182-9671-c775deda1ae7 · outbound

This paper cites Improving Text Embeddings with Large Language Models.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Improving Text Embeddings with Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.848720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.848720Z digest=sha256:01354578237b438fa18a4d5d2271b722cd353e697d995e2d0aea081b0dd40acb

Observation 4998059c-9021-4376-937f-ab499c3ef349 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.854097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.854097Z digest=sha256:368ae3d7fd8186a3b2074ca8c9de2d2ba70658dac41a2192b994b4f652f78a0e

Observation e261ff0b-b28d-4a86-bdfe-55c6f1dea209 · outbound

This paper cites Emergent Abilities of Large Language Models.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Emergent Abilities of Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.859566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.859566Z digest=sha256:5ca9d498f9e8f063bcb4e93d38fd250af90a3eaa738b753f854fc1b080085674

Observation 567f0ba0-d73d-4b7e-b15d-27373ae73c14 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.865187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.865187Z digest=sha256:57335531aa10e4b5f9d9b9cdb506121f0cb1ec4ce8b18ef5d95d94732f6703a1

Observation f0ffa2d1-7c09-483c-b4e4-b73ed4b07302 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval C-Pack: Packed Resources For General Chinese Embeddings

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.869569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.869569Z digest=sha256:756531e0c87e8bdb9b6428c627517ed4d41df809a825a71f7e44d8335fdd94c7

Observation 773f1fc2-52d1-4bcb-8662-60e9d92683ba · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.503984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.875210Z digest=sha256:725d35b2cb2660cc6d8f142c3083017fa8c059f4745fe74ab8fbe11bf9243a22

Observation 072485f9-e771-49cf-8203-670068fa4e99 · outbound

This paper cites SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.880621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.880621Z digest=sha256:8605ba8a0e7d33d072ad525707629557e815d79d1f8e0289fba974dbd0beb7c5

Observation 6c466520-820b-4b12-bb32-87981de0112d · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.886596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.886596Z digest=sha256:b0addac9eaaabaa883d9ffa51eb66440d5c9c52d567b6a1b4ec1ea54ad59c40e

Observation 382279d8-8748-4a65-9f3d-b38aba96f743 · outbound

This paper cites an unresolved cited work.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-12T13:09:40.487238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.892255Z digest=sha256:3c756caa8fc369324bad99dd940453e69b8af31ae40a7634ee351dba3834886e

Observation 51dc1615-effc-4c10-9217-0e760ff35d75 · outbound

This paper cites Kwok, Zhenguo Li, Adrian Weller, and Weiyang Liu.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Kwok, Zhenguo Li, Adrian Weller, and Weiyang Liu

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:09:40.468925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.897766Z digest=sha256:11197d616a55979e45bd5c9020118397200520ac746b0b53bd1d9940810676de

Observation f58731d9-81a0-477a-9e32-b00e713256a0 · outbound

This paper cites Distilling System 2 into System 1.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Distilling System 2 into System 1

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.903092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.903092Z digest=sha256:315809993a437b08c702bf891663e166fd7ba194793808c244d872a3b4fc9534

Observation 634be85a-140e-4e38-8383-8ae438edfaa2 · outbound

This paper cites Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems.

Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T13:09:39.909360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T13:09:39.909360Z digest=sha256:472f35cc7031d00c2c62521b58eb5c6f4fb2ca0e3624979c9df39ab6508cff19

Pith citing papers

Observation 2b7624d3-ec25-4688-9582-fd948de114ee · inbound

LLMs with in-context learning for Algorithmic Theoretical Physics cites this paper.

LLMs with in-context learning for Algorithmic Theoretical Physics Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:31:25.807675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-12T01:00:44.364356Z digest=sha256:fae342a41d45c22947272e74c5cc767071af5f13ca75e8595890823cbe24f1ac

Observation b8a418e6-0268-4908-8e95-7db68282b5d7 · inbound

Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning cites this paper.

Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning Learning by Analogy: Enhancing Few-Shot Prompting for Math Word Problem Solving with Computational Graph-Based Retrieval

Reference 57

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T15:28:33.904924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-27T06:30:55.592334Z digest=sha256:1954a65bb81e94643a3ad36a7c8b32d9f8877781b3dbbab79ece34e3e4617bb2