Paper Citation Record · LEDGER

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement

As of 10 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2508.04289.

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

pith.paper-citation-record.v1
2508.04289 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:48:07.561111Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T10:54:54.558241Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:58:14.149636Z

Reference resolution

18 of 18 outbound references displayed

verified exact0
verified fuzzy12
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0db8a14-d0cd-4a29-8817-d479bcc4e2a0 · outbound

This paper cites Medsyn: Llm-based synthetic medical text generation framework,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Medsyn: Llm-based synthetic medical text generation framework,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:08.753612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1143bea6-0722-4acf-88b4-9d8b4448e9fa · outbound

This paper cites Toolqa: A dataset for llm question answering with ex- ternal tools,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Toolqa: A dataset for llm question answering with ex- ternal tools,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:08.511364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ee386e38-cf65-429d-a116-e8259f7573ad · outbound

This paper cites Structured dialogue system for mental health: An llm chatbot leveraging the pm+ guidelines,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Structured dialogue system for mental health: An llm chatbot leveraging the pm+ guidelines,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:08.385230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fae36fab-c44b-4dc8-8bb3-db3a22850658 · outbound

This paper cites Large Language Model (LLM) AI text generation detection based on transformer deep learning algorithm.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Large Language Model (LLM) AI text generation detection based on transformer deep learning algorithm

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:07.475927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aef42d3d-ca14-47c0-873c-7fc6473bcd9f · outbound

This paper cites Attention is all large language model need,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Attention is all large language model need,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:08.266683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2cc9f174-ea9d-4526-817a-7ed43abe6164 · outbound

This paper cites Efficient llm inference on cpus,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Efficient llm inference on cpus,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:08.097672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fadf5366-2d57-4ea1-9fd3-1971677caa26 · outbound

This paper cites Empowering LLMs with Logical Reasoning: A Comprehensive Survey.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Empowering LLMs with Logical Reasoning: A Comprehensive Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:07.494873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92531a13-9b87-4570-b75f-889429b20cbe · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Chain-of-thought prompting elicits reasoning in large language models,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:07.499858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4b71c8e-872a-4c8c-9986-8afc118926d6 · outbound

This paper cites React: Synergizing reasoning and acting in language models,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement React: Synergizing reasoning and acting in language models,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:07.506789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 451cec02-3f17-4a0a-be7f-fa4faa6a6b26 · outbound

This paper cites Training language models to follow instructions with human feedback,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Training language models to follow instructions with human feedback,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:07.945668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2c19ac71-c0a0-4419-8bcc-1bcf99781cc1 · outbound

This paper cites Retrieval-augmented generation for knowledge- intensive nlp tasks,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Retrieval-augmented generation for knowledge- intensive nlp tasks,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:07.906989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 820d409b-6712-44d7-831c-74df8ce6956a · outbound

This paper cites Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:07.524592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb13600b-d35d-4e52-9857-81a242f73873 · outbound

This paper cites A survey on rag meeting llms: Towards retrieval-augmented large language models,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement A survey on rag meeting llms: Towards retrieval-augmented large language models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:07.866222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b45f392c-300e-4cb9-9365-6f0a424d6f55 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Toolformer: Language models can teach themselves to use tools,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:07.825672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 367f7469-5a30-4bcf-a68a-db7ae2f9f4bb · outbound

This paper cites Extended context for instructgpt with lla- maindex,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Extended context for instructgpt with lla- maindex,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:07.788946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d25b983-129f-4a1d-875e-216e3391e92c · outbound

This paper cites Creating large language model applications utilizing langchain: A primer on developing llm apps fast,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Creating large language model applications utilizing langchain: A primer on developing llm apps fast,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:07.755853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 29bb5a0d-f1d9-496a-8d07-3bcebe649f3d · outbound

This paper cites Unlocking llms’ self-improvement capacity with au- tonomous learning for domain adaptation,.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Unlocking llms’ self-improvement capacity with au- tonomous learning for domain adaptation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:48:07.720356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 48bc25ef-2a26-4214-9521-6ae6d6b0b375 · outbound

This paper cites Large Language Models Can Self-Improve.

Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement Large Language Models Can Self-Improve

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T00:48:07.561111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation e3e4049b-ae13-4ced-9f0b-64bd7b3ba692 · inbound

Code as Agent Harness cites this paper.

Code as Agent Harness Method-Based Reasoning for Large Language Models: Extraction, Reuse, and Continuous Improvement

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:58:14.151385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.