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Paper Citation Record · LEDGER

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.20425.

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

pith.paper-citation-record.v1
2607.20425 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T16:42:05.599412Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c369697a-8e97-4611-a2e5-c2b444636472 · outbound

This paper cites Rhetoric.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Rhetoric

Reference 1

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source=arxiv_source observed=2026-08-02T16:42:05.508517Z digest=sha256:b93775d8e5240b87d961813e1c0ed100f2e3e418ff00bbdf7a9321821b040644

Observation 61cb113e-b34a-457c-9549-c7624dfd74be · outbound

This paper cites The Well Wrought Urn: Studies in the Structure of Poetry.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces The Well Wrought Urn: Studies in the Structure of Poetry

Reference 2

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source=arxiv_source observed=2026-08-02T16:42:05.511598Z digest=sha256:70f34ef3f38f0b79a42863eb20572c18331ecdc43b1908a0d862fff398fb3ac0

Observation e06cae6e-d27f-4765-b382-e87cf38e8761 · outbound

This paper cites Writing with Power: Techniques for Mastering the Writing Process.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Writing with Power: Techniques for Mastering the Writing Process

Reference 3

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source=arxiv_source observed=2026-08-02T16:42:05.515955Z digest=sha256:a51423b835ac4b791fa69f561891c1b6fceb8e0759d92de7b50d637e67027fb9

Observation decf034e-3789-4260-9f11-728ba1142a30 · outbound

This paper cites The Art of Fiction: Notes on Craft for Young Writers.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces The Art of Fiction: Notes on Craft for Young Writers

Reference 4

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source=arxiv_source observed=2026-08-02T16:42:05.518360Z digest=sha256:e31612377e2fd3d3511001cdb5c83ff65c6a6ea07ceee4a1554bfee17d291d63

Observation 1bbd1088-96c4-4e18-945d-cbfeea1a3e5d · outbound

This paper cites The technique of clear writing.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces The technique of clear writing

Reference 5

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source=arxiv_source observed=2026-08-02T16:42:05.520847Z digest=sha256:aa23b3cf78ee90b8dd42afa6958990325eb7fa23c9f0e58703a0b1477a3270d5

Observation 9fb101ef-f88b-4b47-8f3f-86d321dcfd2c · outbound

This paper cites A computational analysis of style, affect, and imagery in contemporary poetry.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces A computational analysis of style, affect, and imagery in contemporary poetry

Reference 6

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source=arxiv_source observed=2026-08-02T16:42:05.523242Z digest=sha256:401d03fa953fe40c6e2ec8bc9c1bcd22532846e2040c4edc000702a35e8e2454

Observation 1d25c4bf-26b3-4592-901a-780762ac35b0 · outbound

This paper cites Automated essay scoring: A survey of the state of the art.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Automated essay scoring: A survey of the state of the art

Reference 7

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source=arxiv_source observed=2026-08-02T16:42:05.525953Z digest=sha256:6bd8dc61e3c2f09b1c10cc199986b7214131263767b53d7b92bf8947dc823c94

Observation 1c459e83-2141-43c1-bd3b-5f081499ca3b · outbound

This paper cites Peter Kincaid, Robert P.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Peter Kincaid, Robert P

Reference 8

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source=arxiv_source observed=2026-08-02T16:42:05.528013Z digest=sha256:984bd8e0601da43570c574bcb1208c94a36ed8f47eebfac81e0956e447fc9be9

Observation 7a12c10c-682d-459f-b4b7-e93a7a49e383 · outbound

This paper cites RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Reference 11

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source=arxiv_source observed=2026-08-02T16:42:05.536035Z digest=sha256:f51ba390ddd04a797f6005f094d7d8afd97ae103a0c886d2318bf2f71b1e9a39

Observation 8817d11e-c11c-4551-89db-de542ecae803 · outbound

This paper cites G- E val: NLG evaluation using GPT-4 with better human alignment.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces G- E val: NLG evaluation using GPT-4 with better human alignment

Reference 12

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source=arxiv_source observed=2026-08-02T16:42:05.538604Z digest=sha256:3dcaf17139588cf17eaebfaa7d9373b13591810b3f0a7423357515e706a1f8a0

Observation da0e4f4f-b16c-4be7-9bec-e4dc83bdd0bb · outbound

This paper cites A survey of modern authorship attribution methods.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces A survey of modern authorship attribution methods

Reference 13

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source=arxiv_source observed=2026-08-02T16:42:05.540798Z digest=sha256:7a8a4af3cd42137d8f3b0a1cf145348d51c310750cfcc3afb025c4a03beba3d8

Observation 5c6e6eb8-661e-4364-9540-9fc307e8eb1d · outbound

This paper cites an unresolved cited work.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Unresolved cited work

Reference 14

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source=arxiv_source observed=2026-08-02T16:42:05.542893Z digest=sha256:fa6666b1b2a6bc82ad75cc4c963c643d7ddee2abe341edc84115d9f2febd1cc6

Observation 7b692412-37ec-4675-bc89-1e19bed8bd88 · outbound

This paper cites A review of deep-neural automated essay scoring models.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces A review of deep-neural automated essay scoring models

Reference 15

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source=arxiv_source observed=2026-08-02T16:42:05.544897Z digest=sha256:c17ce9096deea52f93ce7928015728b0b2de6b89e894c7e0a069e1a4cfd8940f

Observation 3ab980fd-12d8-4aaa-a026-e20a9a180c5d · outbound

This paper cites Wilson and Jonathan W.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Wilson and Jonathan W

Reference 17

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source=arxiv_source observed=2026-08-02T16:42:05.549359Z digest=sha256:e7e2660040c279b9262b783b008349cb1ef841fa7d1608fb7aba1b7546b793ba

Observation 63fcf9a9-4f51-4781-b01e-224645df3e92 · outbound

This paper cites Judging LLM -as-a-judge with MT-Bench and chatbot arena.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Judging LLM -as-a-judge with MT-Bench and chatbot arena

Reference 18

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source=arxiv_source observed=2026-08-02T16:42:05.551488Z digest=sha256:d139dd2fab4dbecc941c0871fa3cba5a4c0013cea8eab5fb498d83a8528c53d4

Observation d62585c6-34df-4826-96ac-49a6b01453ca · outbound

This paper cites -350 , note=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces -350 , note=

Reference 19

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source=arxiv_source observed=2026-08-02T16:42:05.553585Z digest=sha256:5c2d0b628b21c6805f7122c1c7ef4e3a123a0cc9b1a5698cb1c514194dfa0c54

Observation 8239589a-202a-4130-8ccf-2652f2628bb6 · outbound

This paper cites 1947 , publisher=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces 1947 , publisher=

Reference 20

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source=arxiv_source observed=2026-08-02T16:42:05.555952Z digest=sha256:3e387756408db3391f0e64303c986a9cd5bb785a3f45287b9884c9b580638336

Observation 9f1c6965-ca28-45b5-b1d1-48cc88ed00c3 · outbound

This paper cites 2014 , publisher=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces 2014 , publisher=

Reference 21

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source=arxiv_source observed=2026-08-02T16:42:05.557983Z digest=sha256:bf7a133fb2bf37ae45172e728f18eb08ecbe0d1a11197bf550f7a47ffdb64641

Observation d86adfe0-35ed-4af4-969b-4fb3e5ebecdf · outbound

This paper cites 1991 , publisher=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces 1991 , publisher=

Reference 22

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source=arxiv_source observed=2026-08-02T16:42:05.560109Z digest=sha256:dc97284d9ef727c134aef715f7a98b372e6848f5ad496543d8a5d570f0495b36

Observation 13cfe7aa-f514-4268-ad42-f6fcc22bccf3 · outbound

This paper cites 1981 , publisher=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces 1981 , publisher=

Reference 23

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source=arxiv_source observed=2026-08-02T16:42:05.562108Z digest=sha256:742da698207666297a7440b8e1e75d36408a7520f44a7888511d691780c85253

Observation 701a8507-5233-40c4-8ef7-862aea67a44e · outbound

This paper cites Research Branch Report , volume=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Research Branch Report , volume=

Reference 24

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source=arxiv_source observed=2026-08-02T16:42:05.564238Z digest=sha256:c002434ad63e8ebcd78affa2830801f30028a71dc664fec9de7eade200cc117f

Observation fab43e65-a1ef-473c-a49e-40f63036c127 · outbound

This paper cites McGraw-Hill , year=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces McGraw-Hill , year=

Reference 25

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source=arxiv_source observed=2026-08-02T16:42:05.566282Z digest=sha256:d9612dc8d4dd990b364637ff1e49f592adb0579e7a779669fe1a6681fab1980e

Observation b4e50d65-148d-44ad-8bed-75cd2efde0ad · outbound

This paper cites Journal of Applied Psychology , volume=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Journal of Applied Psychology , volume=

Reference 26

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source=arxiv_source observed=2026-08-02T16:42:05.568801Z digest=sha256:60b65c9e4497ddfe2180b30bbd3451cf3cdd44a6da0b4a64f1befe7c6861b3c4

Observation 0edfc99a-5e04-49a3-9ca7-3404418f3fdc · outbound

This paper cites an unresolved cited work.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Unresolved cited work

Reference 27

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source=arxiv_source observed=2026-08-02T16:42:05.571179Z digest=sha256:ae54371e823583e9fc70e449da3506988a7edc684f544c45c9e1932b069588f7

Observation 6270fff8-29cb-4fff-baac-2c5894ce19e9 · outbound

This paper cites RLAIF: Scaling Reinforcement Learning from Human Feedback with.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces RLAIF: Scaling Reinforcement Learning from Human Feedback with

Reference 28

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source=arxiv_source observed=2026-08-02T16:42:05.573344Z digest=sha256:dd531c3b8d5d31b400a5396ee31869b8d5a00ea13679b4827c1c30c8d1fedcd6

Observation de172999-4355-4620-83fb-a5f009870abf · outbound

This paper cites an unresolved cited work.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Unresolved cited work

Reference 29

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source=arxiv_source observed=2026-08-02T16:42:05.575567Z digest=sha256:8e73762768ff89ab22dd63bee0366084eb1a5f39125c67fbc45b649093648f33

Observation 32ab64a9-ccc8-484b-a5fe-bc79565cde51 · outbound

This paper cites Journal of Personality and Social Psychology , volume=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Journal of Personality and Social Psychology , volume=

Reference 30

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source=arxiv_source observed=2026-08-02T16:42:05.577897Z digest=sha256:7126d4760551dd0c924ca5820445346e9bf3a208b5cdbdd6c657edd24cfa1fe0

Observation c59694e7-13df-4d9d-a19b-217b4dc602ce · outbound

This paper cites DeepSeek-V3 Technical Report.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces DeepSeek-V3 Technical Report

Reference 31

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source=arxiv_source observed=2026-08-02T16:42:05.580041Z digest=sha256:05c9ad9bfef512dd0d0c724220f05a5286a247a10ccf4094bec1f5f481ff51cd

Observation daa1f579-d7eb-4d45-863f-f6da53575701 · outbound

This paper cites Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) , pages=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) , pages=

Reference 32

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source=arxiv_source observed=2026-08-02T16:42:05.582511Z digest=sha256:af54a8260fe3b70b716072796c07703baafc893936dc712e6d0cc0e80ff240a5

Observation b1c9bbca-8f3b-498d-9608-17964012af17 · outbound

This paper cites Behaviormetrika , volume=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Behaviormetrika , volume=

Reference 33

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source=arxiv_source observed=2026-08-02T16:42:05.584651Z digest=sha256:eae4309f8f2d4772d4eb4caa53f036b8cb8cdbad66c58d823ee5df8c6eb9bc2a

Observation 2610e3ff-7044-4bcc-9cdc-dffb85963110 · outbound

This paper cites Journal of the American Society for Information Science and Technology , volume=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Journal of the American Society for Information Science and Technology , volume=

Reference 34

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source=arxiv_source observed=2026-08-02T16:42:05.586943Z digest=sha256:ae7679dbb326d6f880959fe98f616e3e88371c7d559febb3ce3317a5796047b2

Observation f3149282-7c40-41ea-a0fc-b864ea2b2712 · outbound

This paper cites Proceedings of the NAACL-HLT Workshop on Computational Linguistics for Literature , pages=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Proceedings of the NAACL-HLT Workshop on Computational Linguistics for Literature , pages=

Reference 35

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source=arxiv_source observed=2026-08-02T16:42:05.589412Z digest=sha256:3b8064454beb930c2dd2db56a60da7bfef0f848dee2db04c02cfd13741aaa018

Observation e674fe3e-ddab-4a68-bb76-2ecfa25e8096 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Advances in Neural Information Processing Systems , volume=

Reference 36

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source=arxiv_source observed=2026-08-02T16:42:05.591574Z digest=sha256:69cebaeb3eb7f7a5df71891e731739dd33322517aea271ac308962c1deeb1fa0

Observation 4ca312a5-2704-4819-a31a-e6bfbfa125e7 · outbound

This paper cites Measuring Faithfulness in Chain-of-Thought Reasoning.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Measuring Faithfulness in Chain-of-Thought Reasoning

Reference 37

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source=arxiv_source observed=2026-08-02T16:42:05.593610Z digest=sha256:44d1199aa1ef6769f89ba4f9102d76f5ab5a2d7005c7a2b09202f307577567eb

Observation 12972055-358b-4597-b986-6c8739118079 · outbound

This paper cites Large Language Models are not Fair Evaluators.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Large Language Models are not Fair Evaluators

Reference 38

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source=arxiv_source observed=2026-08-02T16:42:05.595679Z digest=sha256:e872f6ee21627e6f7257c859b90fa475444f8c7a26288b6daa28dc6da7088d64

Observation 48c6a736-6094-48ba-be94-2cf8e6e86dbc · outbound

This paper cites Benchmarking Cognitive Biases in Large Language Models as Evaluators.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces Benchmarking Cognitive Biases in Large Language Models as Evaluators

Reference 39

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source=arxiv_source observed=2026-08-02T16:42:05.597565Z digest=sha256:1b63f1b8a4dfa36e0caa2490e8c865abbec979393ebbc8e8e46de550dba3987a

Observation f9734478-1514-413e-994c-4ecf1687a209 · outbound

This paper cites On the Limitations of Using.

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces On the Limitations of Using

Reference 40

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source=arxiv_source observed=2026-08-02T16:42:05.599412Z digest=sha256:3c63856205db9b8f823c0838f04e857571f19a547055ed256c3137f57cee337a

Pith citing papers

No inbound Pith citation observations are available.