Paper Citation Record · LEDGER

THiNK: Can Large Language Models Think-aloud?

As of 8 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2505.20184.

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

pith.paper-citation-record.v1
2505.20184 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:04:37.575936Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T22:20:53.998837Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy16
unresolved15
parse uncertain3
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8a7c8880-5fd9-469d-bcb4-c7d5e50c4e4d · outbound

This paper cites By analyzing which concepts are invoked, we assess the knowledge dimension activated during problem-solving and whether the LLM navigates these domains coherently.

THiNK: Can Large Language Models Think-aloud? By analyzing which concepts are invoked, we assess the knowledge dimension activated during problem-solving and whether the LLM navigates these domains coherently

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:43.254905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0fa765ff-d851-481b-a821-0373e1944790 · outbound

This paper cites Thilo Hagendorff, Sarah Fabi, and Michal Kosinski.

THiNK: Can Large Language Models Think-aloud? Thilo Hagendorff, Sarah Fabi, and Michal Kosinski

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:44.055481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a4aa73a5-1796-43c5-aa1f-a76b5d6ed06c · outbound

This paper cites Representations are critical for logical coherence and traceability in reasoning.

THiNK: Can Large Language Models Think-aloud? Representations are critical for logical coherence and traceability in reasoning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:42.892838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2f68695c-0270-47e6-81cb-67b468eebf67 · outbound

This paper cites A model’s ability to adapt its reasoning across such variants reflects generalization ability—an essential attribute of HOT.

THiNK: Can Large Language Models Think-aloud? A model’s ability to adapt its reasoning across such variants reflects generalization ability—an essential attribute of HOT

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:42.649080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9d1a54d-e351-4c68-a515-5b41cb3329af · outbound

This paper cites Five Keys.

THiNK: Can Large Language Models Think-aloud? Five Keys

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:42.396321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 30a63fb8-e0f4-41a6-a468-e77e64a0ac3f · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

THiNK: Can Large Language Models Think-aloud? Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:34.989895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f285043-ceae-4a7e-b7ac-a08237cb27f7 · outbound

This paper cites Assessing and Understanding Creativity in Large Language Models.

THiNK: Can Large Language Models Think-aloud? Assessing and Understanding Creativity in Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:35.188891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eda686bc-321f-44f8-b9d2-085ef43b9912 · outbound

This paper cites Five Keys.

THiNK: Can Large Language Models Think-aloud? Five Keys

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:43.413353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fc6c6ce0-d87c-436f-b349-e6e86497d3cf · outbound

This paper cites These skills serve as proxies for prior knowledge and inform whether the LLM draws upon relevant background competence.

THiNK: Can Large Language Models Think-aloud? These skills serve as proxies for prior knowledge and inform whether the LLM draws upon relevant background competence

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:43.061734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bc43f647-0c80-4f11-92ad-366e129e0133 · outbound

This paper cites You should try to understand and retrieve the specific mathematical information in it such as facts, patterns, objects, or contextual information, and decipher these meanings.

THiNK: Can Large Language Models Think-aloud? You should try to understand and retrieve the specific mathematical information in it such as facts, patterns, objects, or contextual information, and decipher these meanings

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:42.080713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f80c2551-b0ae-441d-87f4-f27be7b9cd08 · outbound

This paper cites It includes understanding and organizing information, analyzing relationships, drawing conclusions, and distinguishing nuances.

THiNK: Can Large Language Models Think-aloud? It includes understanding and organizing information, analyzing relationships, drawing conclusions, and distinguishing nuances

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:41.709139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 632569ac-4052-4187-86a6-dc67e329e041 · outbound

This paper cites These new expressions should have the same form as the given expressions in the previous generated math problem.

THiNK: Can Large Language Models Think-aloud? These new expressions should have the same form as the given expressions in the previous generated math problem

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:41.478200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d90fac4d-e73b-47fc-bc1f-49e61c612496 · outbound

This paper cites The generated stories must be a mathematical word problem with the corresponding expressions.

THiNK: Can Large Language Models Think-aloud? The generated stories must be a mathematical word problem with the corresponding expressions

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:41.250540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ae966b1-69d3-4983-b64b-2753e21a22c2 · outbound

This paper cites question.

THiNK: Can Large Language Models Think-aloud? question

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:40.942421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d7221b4a-69f1-4292-9c7e-b07d16682968 · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:40.731850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 097e0f7a-e8c0-4aa7-8a53-1112802d3640 · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:40.516278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e7cca71a-fa57-4018-81a1-996ea4f8a584 · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:40.346332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71cfc3bd-c73a-4638-a83b-201870d4932c · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:40.119981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0bd16435-849c-4b77-b423-35024e0a2a0d · outbound

This paper cites ID": null,.

THiNK: Can Large Language Models Think-aloud? ID": null,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:39.859244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 905ea987-80e9-4efc-ac45-90783e9ccf18 · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:39.683488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 373900a1-c4ed-414f-acab-352e4fb4840a · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:39.422480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 28bbc1f8-ccd1-4e0f-a597-8346676859cb · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:39.228336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79f727b5-a1b4-4900-b207-266a76810f5d · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:39.013489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fba5fb64-1ef4-447e-8f46-3851e00a2fc2 · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:38.843275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation daaf974f-20f5-4e54-9b92-d6d3073a526b · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:04:38.604568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 88110793-a66b-414c-aaa9-dd9f02d9fef1 · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 31

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T14:04:38.445619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation acfc7e07-2c28-4479-9c14-bb5374b74b76 · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 32

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T14:04:38.191305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 237518b0-cf69-410d-8cfa-93d6a34f5c0c · outbound

This paper cites an unresolved cited work.

THiNK: Can Large Language Models Think-aloud? Unresolved cited work

Reference 33

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T14:04:38.000547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7735d87f-a2ae-410b-84eb-b1424ad23de3 · outbound

This paper cites performance_score.

THiNK: Can Large Language Models Think-aloud? performance_score

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:37.798360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6e3bc5a6-54ea-4d38-a129-9d44eba41060 · outbound

This paper cites English language teaching, 3(4):237– 248.

THiNK: Can Large Language Models Think-aloud? English language teaching, 3(4):237– 248

Reference 2010

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:43.595243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4f4a0605-e26a-479d-bef5-6bda3f3c3127 · outbound

This paper cites MulCogBench: A Multi-modal Cognitive Benchmark Dataset for Evaluating Chinese and English Computational Language Models.

THiNK: Can Large Language Models Think-aloud? MulCogBench: A Multi-modal Cognitive Benchmark Dataset for Evaluating Chinese and English Computational Language Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:35.106825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93bfd8cb-0986-4884-9228-76953960d739 · outbound

This paper cites HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models.

THiNK: Can Large Language Models Think-aloud? HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:34.719074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6c0dea8-bcd4-4dcd-8b03-81fbd12f337b · outbound

This paper cites TOFEDU: The Future of Education Journal, 3(5):1488–1499.

THiNK: Can Large Language Models Think-aloud? TOFEDU: The Future of Education Journal, 3(5):1488–1499

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:04:43.817646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e335ab1c-82d5-46d0-9b99-a5dfdcb741e1 · outbound

This paper cites Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks.

THiNK: Can Large Language Models Think-aloud? Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:34.565123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 13673311-eda7-400a-b9d2-8c8c39141232 · inbound

Mechanistic Interpretability of Cognitive Complexity in LLMs via Linear Probing using Bloom's Taxonomy cites this paper.

Mechanistic Interpretability of Cognitive Complexity in LLMs via Linear Probing using Bloom's Taxonomy THiNK: Can Large Language Models Think-aloud?

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T22:20:53.998837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.