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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 14 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 2026-08-14T06:32:32.682623+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=sha256:083e4335c36b0356fd2544e3eb3133f65aaa3799d8757039287fbaf1e0115f26

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

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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=sha256:1d7a69767760a0bbfbe96c1a2602e18d3ee85c1215118a29ce2190531b94b44e

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.656073Z digest=sha256:9cba80fdc736bcd93eadea809bde33965f1a8ddbb5aeb0735a8049bbbbd3bb8a

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=sha256:07aa7a5e1547739358d58f48d8cf68c9956da3939e2dfeab3515ecdd7d0078cd

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

Resolution
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=sha256:2a8c528fbf53a808a55ab3d7948ee28b9a42805d12f4e3a3ba1b086fe9499ee1

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=sha256:5b11ea504ab0986b0349a4b18f94f021acf273393f375a93a28b742052c39329

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=sha256:703492c9f6695b9f79035d26facc741060ffa63d9f239d52413c440fe835caef

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.684963Z digest=sha256:3212c6efce19c14da24f1b1e7b722207b14564276067027d16ea4798e0bd2e61

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

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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=sha256:5ae2568885e54917c9a9e0ad32bcbef6af3ae8feac45b893e3d75d8cd68541bc

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:aecca26d6d4f3324fbc2208d32250e9e067f17730f02caafa5e884c26f2425ab

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=sha256:69657dad88dd58dc2fb29a14983bf84bd89967ac0d9901a5cbc7b158f72a2f1f

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:b0585caab05b762eeff0a9b2632ab9672344119aae4092e5a70dbf25bf8a4027

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=sha256:5939ad2345cc26d21f8a2b3d7e587b5284f0730124bceb0a32fcfa0e97e5f650

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=sha256:1f1f6960bdce99e03511802900ef596f8d02c46bf19d772763bdd8eb2b50ae52

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=sha256:22fffde77afee54d4debee4a75989b7db641aa170e2c3d3b7a16a7899a2c5b35

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:fb0552bbaf3c3f7bb45253adcf1222ff0061b628486e878eefa918e819c89b88

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.734160Z digest=sha256:4abb06847c2476ac50e42c05d85973571de46b14458c00e7001fa32b2c8c7eb5

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 2026-08-14T06:32:32.682623+00:00.

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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
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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=2026-08-12T13:09:39.743712Z digest=sha256:d231ac967e14604b1bfd2240cec6010e3432422d640a670ce8184262a1c2d2a0

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=sha256:75d251a951a34709486be2172bf0eba75e4a35587235d708bcdd539ad875e7d8

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=sha256:7343de98904a7c1b06cbda65502c60992d33b939a692f6e9df7525784dcdafb7

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

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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=sha256:7cce71bcfdb6bd299917058c4f8ce76028edf2ba4defaf59bdc5429e3f59a28c

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=sha256:7995235d1838163087769987be3df5b104d737a8ec6a081b67a07061b7d2bbdd

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=sha256:283875227dc8e33dbc5ed927ff373a43199692bcf6031e909b43e0fc26ca1030

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=sha256:6e325725121cdc6ed2a224acff62fe57902f4b2881da1d1288ab826c633a04c5

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.780735Z digest=sha256:0b9c0ffaf65ab1919e4ca88b358b8be4441877281263cbe73bd2d55df8cbe527

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.785623Z digest=sha256:0d5e9ac4ce70a6f2a738b8129c1e19d62b85a2ee0cabe7c1a88c8f775dba41f6

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.790592Z digest=sha256:a5d559dd18d190235fb4d2d5a68d1338e5aa2b296aa5b33c55fde2d2db07671f

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:b8b3b03dd40cee8aa909136346651a0056b92964306c63f97a7badaba1697e4a

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=sha256:346425f63f79e9a0a7df2f0ff9bdb86ffed82ee2cf8150f52b0c201583ba072f

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.

source=arxiv_source observed=2026-08-12T13:09:39.804827Z digest=sha256:70bc96cb84809152ab027cec9111dd7fcbe0b18454694db205bc407d8832211a

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=sha256:05906992bc79dc9ea74bbeac91cdca0281d8007ab1c6da3829a1fbd72a5dec47

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=sha256:3aef8b95a46ad9b68e45ad87acc8ebb31d7b579287cef6b38947cb0db6d892dd

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:eeeb71dea378d95881ec6c38082ba09ae778530377b48646b41de7d13b7fd632

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.827588Z digest=sha256:b914aed6a5b16cd21eaad708c6f1d3b122f5a2b89b438a5a3e13b41de52cd7a3

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:eb36ed872a1b817ed312dbfa13b0aa344f6c7a4fc4a82a5b582772e40b58499e

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.837767Z digest=sha256:ac791996c38625703ee1329f3bd3b792eec048304bbd94c3d2400b5471aa7071

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:a112311486ee289976d90cd02326732c9cfd4e0b8ab5843bb7ed3506bff158c7

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=sha256:01db348f1242ed809212752026ee24f88121e9d2247db8f04eef8972b50ba188

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=sha256:116cd56934f17ec66ca346e3351da951b31b13efd915730f5be2ecf35988c2e9

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=sha256:15266c1ad43c66ccebb64de06420768d8efc26d045fb522423ac4576f49efbb4

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=sha256:15df3879f03223d3e7a70b0f04a1cdb8c9c56b295dbc3c3bcb75b6c9fe092d7e

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:a23b7d78a593d4fb7418edf4929a532b12a518106947c2a1f9af1e0fad32ffc6

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.875210Z digest=sha256:df58f9c8f8f08ad07d7cb6df7846a280a9dbf316aadd71ec9351b48843d6601d

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=sha256:3066a9d709db76c4ec0d87fc9e971545c06e96c3599de61ace761a78bf82a18c

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=sha256:73b4ba83645fd3a7198fedd30be61da961025b913338ebed4bf52c1e89d8a986

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.892255Z digest=sha256:808332a5660fc44df6ede0750d6917c8d0d051218fae43d019e0ac461f84115c

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-12T13:09:39.897766Z digest=sha256:00cb2abbcefe94bda3b7ca2be7c35b0e44f8bccb1b2615af95ea6af2b49ffeeb

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=sha256:52d50fb342a3c3a89c163bb453fbc4fd02c73b5840b5f6bfbd4ea1ce5c65bdb0

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:beec1463c37f64c71725c06e110fdc912bc1718d957145bd85b44e89aa6aceba

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-12T01:00:44.364356Z digest=sha256:70f02f1285c8c260d6f505463af6450195b90f41e7b10e571c7c9e77ce81a44c

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-27T06:30:55.592334Z digest=sha256:ec91f8a9c5d8a7a163d858ebf46e6fca4b02ffc6e09828809c848e0004790871