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Paper Citation Record · LEDGER

NeuroCogMap Reveals Cognitive Organization of Large Language Models

As of 7 August 2026, this Paper Citation Record lists 100 of 164 outbound references and 0 inbound Pith citation observations for arXiv:2607.00397.

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

pith.paper-citation-record.v1
2607.00397 v1

Coverage vector

measured 100 of 164 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-02T02:36:32.233113Z

measured 100 of 100 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 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

100 of 164 outbound references displayed

  • verified exact9
  • verified fuzzy88
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5ec4444d-759d-40a7-8c22-9ed38623972c · outbound

This paper cites Neuroscience- inspired artificial intelligence.Neuron, 95(2):245–258.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Neuroscience- inspired artificial intelligence.Neuron, 95(2):245–258

Reference 1

Resolution
verified fuzzy
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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.

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Observation 21cf2487-8c95-43d9-98fe-45abfd27fedd · outbound

This paper cites A deep learning framework for neuroscience.Nature neuroscience, 22(11):1761–1770, 2019.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A deep learning framework for neuroscience.Nature neuroscience, 22(11):1761–1770, 2019

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.169119Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:882e9ae92db04c652a3b5bda4844c88bf8a2183ab3b5264181f94c480dcd4de7

Observation 5206ec6b-470f-45d9-90ff-a951989e62f5 · outbound

This paper cites A survey of large language models.Frontiers of Computer Science, 20(12):2012627, 2026.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A survey of large language models.Frontiers of Computer Science, 20(12):2012627, 2026

Reference 3

Resolution
verified fuzzy
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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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:139944eee12be1a08822b3cfbbee06e481ed4aab6cfa7f369d6af463fe0ca9e2

Observation 9e36958b-f220-4b10-b512-35a2c3f9f260 · outbound

This paper cites Deep neural networks as scientific models.Trends in cognitive sciences, 23(4):305–317.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Deep neural networks as scientific models.Trends in cognitive sciences, 23(4):305–317

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.236096Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:cc120f9e39a8397a64687443eda807ec680e1c5c2449cd8f98b4060ae1c0286e

Observation 2c2d4fa5-bd15-4748-943e-e7a22a50a595 · outbound

This paper cites Evaluating large language models in theory of mind tasks.Proceedings of the National Academy of Sciences, 121(45):e2405460121.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Evaluating large language models in theory of mind tasks.Proceedings of the National Academy of Sciences, 121(45):e2405460121

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.119281Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:c0d219a189a6513250ed8e806c625c731ed48cb7feb76da174e4471a5cdc4ce7

Observation 292f7130-4f19-403e-9a77-826cc9b1b035 · outbound

This paper cites Larger and more instructable language models become less reliable.Nature, 634(8032):61–68, 2024.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Larger and more instructable language models become less reliable.Nature, 634(8032):61–68, 2024

Reference 6

Resolution
verified fuzzy
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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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:3f3c43e193bce4be95606ad7a0fe55bcafe70daa0c7ae157d90bcb0df7967a50

Observation 31a09fb4-0524-4267-8ed2-c782a5e6d8fa · outbound

This paper cites Language models transmit behavioural traits through hidden signals in data.Nature, 652(8110):615–621.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Language models transmit behavioural traits through hidden signals in data.Nature, 652(8110):615–621

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.085406Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:e2ea70a72d170afa59b05c449177cfa0d30d53dff3199e494500d6f2fe8fb704

Observation f80926d9-0b05-4d86-a622-d154996f20b1 · outbound

This paper cites Vempala, and Edwin Zhang.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Vempala, and Edwin Zhang

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.941978Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:5d99378218ef0aa303efc3cfba8075a919654117184d4d4397222983c1a2e6d2

Observation 49c8d556-528f-4f25-9d25-d9036e1accbf · outbound

This paper cites Knowledge neurons in pretrained transformers.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Knowledge neurons in pretrained transformers

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.996522Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:4b64438821a5ae6c57e59f6d33bda2619367e1648aabf9fd1ea8a3b8efa82bb1

Observation fb5cd787-7fe9-4594-ad17-626561d241d8 · outbound

This paper cites Sparse autoen- coders find highly interpretable features in language models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Sparse autoen- coders find highly interpretable features in language models

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.207146Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:65ff5924c92f3b924c08f694764783bb6ac3e88ff6fdca737cb2c07c87320347

Observation 779fc4a8-b191-4459-b725-b1f7e2b25dfc · outbound

This paper cites Toward universal steering and monitoring of ai models.Science, 391(6787):787–792.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Toward universal steering and monitoring of ai models.Science, 391(6787):787–792

Reference 11

Resolution
verified fuzzy
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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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:cbcf0ba8a3a0cb5adad029d2bc9dd92a7266bce74034fc1c110723255452a186

Observation 8e1dfcdd-a09a-40f8-952c-cb1f0f7ca38e · outbound

This paper cites Causal abstraction: A theoretical foundation for mechanistic interpretability.Journal of Machine Learning Research, 26(83):1–64.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Causal abstraction: A theoretical foundation for mechanistic interpretability.Journal of Machine Learning Research, 26(83):1–64

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.944062Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:f6e298fbb1990b9a88acf803425a4d6303cf6fba8cfb90fb7ee193a4fb6cb9cf

Observation ce68f14b-466e-4db4-bcb1-3bdd9a1d7340 · outbound

This paper cites Mechanistic understanding and validation of large ai models with semanticlens.Nature Machine Intelligence, 7(9):1572–1585, 2025.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Mechanistic understanding and validation of large ai models with semanticlens.Nature Machine Intelligence, 7(9):1572–1585, 2025

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.182943Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:dd139e88f297de880b44a9d5f66307bb9acf890cbb1359ff894aac70240911db

Observation f8a257a3-051c-4c63-a471-66d99281ee06 · outbound

This paper cites The organization of the human cerebral cortex estimated by intrinsic functional connectivity.Journal of neurophysiology.

NeuroCogMap Reveals Cognitive Organization of Large Language Models The organization of the human cerebral cortex estimated by intrinsic functional connectivity.Journal of neurophysiology

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.133916Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:05b83221db400ef25a03dfcb3edb633f6aea22039cd3d0a9aa68b2750891aa1a

Observation caa3f98c-7d65-4c9c-9a89-09dcfa4e922b · outbound

This paper cites Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity mri.Cerebral cortex, 28(9):3095–3114.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity mri.Cerebral cortex, 28(9):3095–3114

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.216560Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:605321a3774022926573b9b95ce78e81a12e6fa8a871e49a0c493ee719560b9c

Observation 1038004a-e042-4824-9add-e2089c57daef · outbound

This paper cites A multi-modal parcellation of human cerebral cortex.Nature, 536(7615):171–178, 2016.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A multi-modal parcellation of human cerebral cortex.Nature, 536(7615):171–178, 2016

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.142474Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:a3962f1fec2e03018995681a925975c3efc4e9353767b32565bced7a36b2a1dd

Observation a19b2a4a-5cd2-425f-8a59-2ed76d274dd2 · outbound

This paper cites Natural speech reveals the semantic maps that tile human cerebral cortex.Nature, 532(7600):453–458.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Natural speech reveals the semantic maps that tile human cerebral cortex.Nature, 532(7600):453–458

Reference 17

Resolution
verified fuzzy
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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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:8471b3a934f214853b1d737d2f44e7523f722031bb842b4a1fdca0c9eadc5d23

Observation a4897c0c-2706-4227-8a4b-04e8d2b5ffdd · outbound

This paper cites Human cognition involves the dynamic integration of neural activity and neuromodulatory systems.Nature neuroscience, 22(2):289–296, 2019.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Human cognition involves the dynamic integration of neural activity and neuromodulatory systems.Nature neuroscience, 22(2):289–296, 2019

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.046909Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:dc94b245c16c7cd348c9b6bbfe4d07db0c7b2c200103447e0d32c08d77659fd7

Observation b367c7a0-05ba-4630-9b4c-d98aacbb0944 · outbound

This paper cites Bloom’s taxonomy of cognitive learning objectives.Journal of the Medical Library Association: JMLA, 103(3):152, 2015.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Bloom’s taxonomy of cognitive learning objectives.Journal of the Medical Library Association: JMLA, 103(3):152, 2015

Reference 19

Resolution
verified fuzzy
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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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:71edb84eeaaefb350906177a9cc84738edf80e8a3361bf64c43abcbed1150f59

Observation 06cf28ad-e7f7-4b64-bda3-a735b0604d03 · outbound

This paper cites Using human brain lesions to infer function: a relic from a past era in the fmri age?Nature Reviews Neuroscience, 5(10):812–819, 2004.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Using human brain lesions to infer function: a relic from a past era in the fmri age?Nature Reviews Neuroscience, 5(10):812–819, 2004

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.052485Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:27e4a1ece92d072b1c21dc70cbedb34054177660189a840b2f69ec0c610bcf43

Observation f04907c9-a6f6-4c75-812b-8ae86d011093 · outbound

This paper cites Locating and editing factual associations in gpt.Advances in neural information processing systems, 35:17359–17372.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Locating and editing factual associations in gpt.Advances in neural information processing systems, 35:17359–17372

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.209093Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:f01f1b8922351be7d48be1cd069420508b9f4f42f17cc216831b788645ec6d7e

Observation a0afe7bb-a4bc-4bcc-a5f3-fe8f1a056735 · outbound

This paper cites arXiv preprint arXiv:2511.13653 , year =.

NeuroCogMap Reveals Cognitive Organization of Large Language Models arXiv preprint arXiv:2511.13653 , year =

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:46:27.597236Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:95b04228a0d417ff03f95cc46731e1a4e581c7d30f85d612ae9036a12133ff49

Observation 113b6a71-c816-4086-a127-943960d8b853 · outbound

This paper cites Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.018985Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:383ebff054bb89774dad2ecd5091071599d8b8aae6d2a49c8d73c1b90a65f027

Observation f54e3568-1c2b-4b81-a0af-815070e95f3b · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-07-02T02:46:27.633453Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:c462b151b651b44faa346d87a09a82500f50018ab51850f843395db701e96f9f

Observation f592d6d9-bfc5-41d6-86e5-ab03be3e967e · outbound

This paper cites The Llama 3 Herd of Models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models The Llama 3 Herd of Models

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-07-02T02:46:27.623853Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:03881e8ff39b7bc6637c96fb9baf58c7661d59afe888aac8a6bcf8f1b5b7cae5

Observation 89daac50-b2b4-4c2a-9453-c027c0c19fca · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Pythia: A suite for analyzing large language models across training and scaling

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.212979Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:a364cbc2dc4be9f9a1f3c755102a2df6d7cd4beb23e39ef6a260f91a60ebdc41

Observation b4f7aeb6-db38-44bd-9a0c-98011fb0fa4f · outbound

This paper cites Truthfulqa: Measuring how models mimic human falsehoods.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Truthfulqa: Measuring how models mimic human falsehoods

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.167286Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:d338b9dd8e38b6b7bc498caf8edbb9a29611db3dde06ff765c91bb9ab2eece9f

Observation 4c6544b7-15d6-4a53-a1ac-a7550e5c4726 · outbound

This paper cites Latent retrieval for weakly supervised open domain question answering.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Latent retrieval for weakly supervised open domain question answering

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.222580Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:78034f59f329104e14deb84bc04819bb70cf8327e6aa0cdc511eb12afd671b9a

Observation f6ae732e-a19d-4d6e-994b-e9dc60d3f6f1 · outbound

This paper cites Halueval: A large-scale hallucination evaluation benchmark for large language models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Halueval: A large-scale hallucination evaluation benchmark for large language models

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.179150Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:11cbbdfcfa1b182a122f1a17d5c5eaad3ddb5358e60ff6bccb7c9814cf8bb4d1

Observation 4e865007-35ca-47be-a828-1adab96f5e67 · outbound

This paper cites Medhallu: A comprehensive benchmark for detecting medical hallucinations in large language models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Medhallu: A comprehensive benchmark for detecting medical hallucinations in large language models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.110357Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:094509e0ffcadf12e88540b36e856bdf79195516960f523857f9b8c272b125ef

Observation be1349d2-0f72-4d11-b50b-768c777da7e9 · outbound

This paper cites Free dolly: Introducing the world’s first truly open instruction-tuned llm.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Free dolly: Introducing the world’s first truly open instruction-tuned llm

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.056161Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:39dc7c9fd2080b92e4f2de3f3825e77220613ee5dbc48039eeb5cf60000603ae

Observation 20218b10-3fe1-48b9-b865-04d79a4bc478 · outbound

This paper cites Crowdsourcing multiple choice science questions.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Crowdsourcing multiple choice science questions

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.122968Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:9bf6ec0d3cb0f21bec4659796a0203cfa055065b60660bd6fc62c9794869d25f

Observation 424a3bc4-3c0e-49cb-8f6a-89dc0b9a4fc6 · outbound

This paper cites Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.130124Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:0085bd50cf06b5e9268a97225f95af31817e3ccb3ec95aab729542ed660c212c

Observation dcb1a086-d835-4f3c-b2f1-c310f718cdeb · outbound

This paper cites arXiv preprint arXiv:2509.03531 , year=.

NeuroCogMap Reveals Cognitive Organization of Large Language Models arXiv preprint arXiv:2509.03531 , year=

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:46:27.618529Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:f944ad2e99a3e8bb96645a23db236a31d5a463cdac4a4d05b4c6f857b37ea776

Observation 1a726293-0ea2-4e57-8281-e877b3ccaaf4 · outbound

This paper cites Uncertainty estimation in autoregressive structured prediction.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Uncertainty estimation in autoregressive structured prediction

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.968172Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:9255e57dc24d3b292218c3f451eddf0097bdc9fa610df0f9605bf1f4a76f6f5f

Observation a7c6dfdd-5eb3-4c7b-8d77-4acfa6998e8b · outbound

This paper cites Out-of-distribution detection and selective generation for conditional language models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Out-of-distribution detection and selective generation for conditional language models

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.005993Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:fc64e31da4ce70e33803cf04e1b9e1e0f2a85a1220dbcbd01d9382162112b6fe

Observation 5a4a2340-bf00-4a49-bc4e-78298689d408 · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.068067Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:6a99c73726778ebd365a842e9b9c2c3862953cb075c907266acf6e085f50120b

Observation 879be88d-775f-4df9-944a-86529eebeb60 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-07-02T02:46:27.603062Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:b42924a990cfc6103e4c7f186f2b1cfb7d0decc303caa5ff893a1109d762a5f9

Observation a808f046-b5ae-4420-af62-a43ab74089a4 · outbound

This paper cites Jailbreakbench: An open robustness benchmark for jailbreaking large language models.Advances in Neural Information Processing Systems, 37:55005–55029.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Jailbreakbench: An open robustness benchmark for jailbreaking large language models.Advances in Neural Information Processing Systems, 37:55005–55029

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.077759Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:42a9bd6f7d52bdb5c6f6f75880ce7509343059b64fadd75d42991470af19ed33

Observation acaed70e-9700-426c-9acd-cf2d80efff6e · outbound

This paper cites Baseline defenses for adversarial attacks against aligned language models, 2024.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Baseline defenses for adversarial attacks against aligned language models, 2024

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.239851Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:e92dd671decfae956449c7061140d4adb9e40aff5c965e8577baa4ba5ea8aedc

Observation a4ccdd58-d73f-4fa8-bfef-8732558e544b · outbound

This paper cites Single- pass detection of jailbreaking input in large language models.Transactions on Machine Learning Research, 2025.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Single- pass detection of jailbreaking input in large language models.Transactions on Machine Learning Research, 2025

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.201410Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:f7b41cba6c07f43aa4daaa1246b85bb352857de77acf1f7b4957f85addfff6d9

Observation 18c9dad8-83c8-48ba-9c26-b3614dfc0502 · outbound

This paper cites Smoothllm: Defending large language models against jailbreaking attacks.Transactions on Machine Learning Research, 2025.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Smoothllm: Defending large language models against jailbreaking attacks.Transactions on Machine Learning Research, 2025

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.113844Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:96c149e9dbfa275835842b5dc171f5a73edc78fe107730a00c01fb342bd88828

Observation 125f7678-fb55-49c2-8212-cf820d9d814c · outbound

This paper cites The neural architecture of language: Inte- grative modeling converges on predictive processing.Proceedings of the National Academy of Sciences, 118(45):e2105646118, 2021.

NeuroCogMap Reveals Cognitive Organization of Large Language Models The neural architecture of language: Inte- grative modeling converges on predictive processing.Proceedings of the National Academy of Sciences, 118(45):e2105646118, 2021

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.199527Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:05918f175ffceb135b7e5cc1145670337f0602d50f52bde168d4f95c155473f5

Observation c7316571-e32b-4706-9e82-b62b1fc0a84e · outbound

This paper cites Shared functional specialization in transformer-based language models and the human brain.Nature communications, 15(1):5523, 2024.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Shared functional specialization in transformer-based language models and the human brain.Nature communications, 15(1):5523, 2024

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.050565Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:5b37433ccf5d839074b2314a0362d3f591f1e3aca8badd4f5a215d03b199cbb6

Observation 87113ab7-ea3e-42ed-9736-9d22748c6793 · outbound

This paper cites Increasing alignment of large language models with language processing in the human brain.Nature computational science, 5(11):1080–1090, 2025.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Increasing alignment of large language models with language processing in the human brain.Nature computational science, 5(11):1080–1090, 2025

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.982659Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:892ed0dacfddcb0b012fb5f777df1fded68e5e5419764297454faede7fab6f16

Observation bfc8bba7-4dac-4cc2-9eaf-6749d73450f7 · outbound

This paper cites Instruction- tuning aligns llms to the human brain.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Instruction- tuning aligns llms to the human brain

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.952224Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:1d85ec2e5087a9caee3091120c2f9f500e44e3317b89772ebfec2a416a379c78

Observation cf665cc9-3784-4b43-b1d5-da3bf87c239b · outbound

This paper cites A natural language fmri dataset for voxelwise encoding models.Scientific Data, 10(1):555, 2023.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A natural language fmri dataset for voxelwise encoding models.Scientific Data, 10(1):555, 2023

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.990283Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:d472f0a65720de64702a872af8c6dd8bd2a927534adecac1ed871dfb787bf886

Observation 6c4332e0-2ef4-494e-83c0-22df26193060 · outbound

This paper cites Toward a universal decoder of linguistic meaning from brain activation.Nature communications, 9(1):963, 2018.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Toward a universal decoder of linguistic meaning from brain activation.Nature communications, 9(1):963, 2018

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.121214Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:e701072278d87bd0a1334249e7f6d4110fa2d8ee742fa04f4be4b277288915a5

Observation 3c8c3a84-51b5-415f-864e-41e1e2622a08 · outbound

This paper cites Bert: Pre-training of deep bidi- rectional transformers for language understanding.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Bert: Pre-training of deep bidi- rectional transformers for language understanding

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.022812Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:8e9f8c9a5f630a3be64315fff601eaf4ad7068a1e00240f866572c1ffebad358

Observation a266e660-ab58-4c68-ab14-9cd3afbd0092 · outbound

This paper cites LITcoder: A General-Purpose Library for Building and Comparing Encoding Models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models LITcoder: A General-Purpose Library for Building and Comparing Encoding Models

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-07-02T02:46:27.626412Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:fa96a5c05d5bb420dbf06fcb30705b239fe528b82b0b12e13d93076982902a10

Observation 5efa0620-b701-4776-a522-96845f70451d · outbound

This paper cites an unresolved cited work.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-07-06T09:02:13.156252Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:fff4796a42b1a103bef2fb901ba6015459e79a00746d0e625015f8503e587ffc

Observation 56f715fc-6b87-4d9a-8b7d-b739de11facb · outbound

This paper cites Mapping neurotransmitter systems to the structural and functional organization of the human neocortex.Nature neuroscience, 25(11):1569–1581.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Mapping neurotransmitter systems to the structural and functional organization of the human neocortex.Nature neuroscience, 25(11):1569–1581

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.966391Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:91ca46217ed8aefd94185dad37f3cf19ba0a1cf61f09e8a0ada55e5ed450c6c9

Observation db996d5e-a62c-4a52-bf9c-c10d7bf6a4a1 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-07-02T02:46:27.614699Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:19afbc6d324dd8e026ff7a7b3e924d897b81e9bf0e8ac60f15526bcab038d49c

Observation bc49cee6-074a-4e0f-9170-df9ccee65207 · outbound

This paper cites Representational similarity analysis- connecting the branches of systems neuroscience.Frontiers in systems neuroscience, 2:249, 2008.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Representational similarity analysis- connecting the branches of systems neuroscience.Frontiers in systems neuroscience, 2:249, 2008

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.231954Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:03b71177c2a27cea01b150cdddee2243417fcaf59125cc67ec476e1564d83f7f

Observation 53f21f2e-8d97-47e6-8bee-89e585e6149a · outbound

This paper cites Rethinking model-based and model-free influences on mental effort and striatal prediction errors.Nature Human Behaviour, 7(6):956–969, 2023.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Rethinking model-based and model-free influences on mental effort and striatal prediction errors.Nature Human Behaviour, 7(6):956–969, 2023

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.103004Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:5a434c955fa01d3cd3d8c26e4397a517dcdafe0860aa83753bea25471edf02bc

Observation ffd4c91e-7768-4d4c-ab18-f92d1700047b · outbound

This paper cites When does model-based control pay off? PLoS computational biology, 12(8):e1005090, 2016.

NeuroCogMap Reveals Cognitive Organization of Large Language Models When does model-based control pay off? PLoS computational biology, 12(8):e1005090, 2016

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.956188Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:c6ef4454a638b1cf46ceea390d5f33e6646378ee62e625dac31d2c0a417b43f2

Observation f601ec4c-3cb5-4f0f-9c5d-40bf7394e881 · outbound

This paper cites Cost-benefit arbitration between multiple reinforcement-learning systems.Psychological science, 28(9):1321–1333, 2017.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Cost-benefit arbitration between multiple reinforcement-learning systems.Psychological science, 28(9):1321–1333, 2017

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.992469Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:db3f116943d567bd6bd426f2cb17337dad7e6d27faa878acf1c23a0a1f7a5f64

Observation 6c246eff-8ed2-4e64-826b-bc29678e4e77 · outbound

This paper cites A foundation model to predict and capture human cognition.Nature, 644(8078):1002–1009, 2025.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A foundation model to predict and capture human cognition.Nature, 644(8078):1002–1009, 2025

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.066088Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:70c3463ed003a32204ef658aea54c44c3a62fcaf1f5c6025771dda4b0bb72d11

Observation b1527f10-09b6-4360-8e9c-2dc87928aac5 · outbound

This paper cites Model-based fmri and its application to reward learning and decision making.Annals of the New York Academy of sciences, 1104(1):35–53, 2007.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Model-based fmri and its application to reward learning and decision making.Annals of the New York Academy of sciences, 1104(1):35–53, 2007

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.999782Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:426fdd2720e43669bdcf76f61b532b89a44b7e626653a2ae9041ef8baea422f2

Observation 99cd60d9-20e4-4b0b-ab57-ad5b2736d68d · outbound

This paper cites States versus rewards: dissociable neural prediction error signals underlying model-based and model-free reinforcement learning.Neuron, 66(4):585–595, 2010.

NeuroCogMap Reveals Cognitive Organization of Large Language Models States versus rewards: dissociable neural prediction error signals underlying model-based and model-free reinforcement learning.Neuron, 66(4):585–595, 2010

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.010685Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:466fc628cf393662d096e64e14c4fda42d54e00f62f39c60adcf64465bab2a3e

Observation f7348aa6-8d3a-4891-864d-48487aef4166 · outbound

This paper cites Model-based influences on humans’ choices and striatal prediction errors.Neuron, 69(6):1204–1215, 2011.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Model-based influences on humans’ choices and striatal prediction errors.Neuron, 69(6):1204–1215, 2011

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.158261Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:b781f876448dd6fd6e3bf11112546bd1a83387c7da42bbc635dace7b4756f1cc

Observation d73fd02d-540b-448b-bfe5-6f8cdb87689b · outbound

This paper cites Intent matters: Resolving the intentional versus incidental learning paradox in episodic long-term memory.Journal of Experimental Psychology: General, 152(1):268, 2023.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Intent matters: Resolving the intentional versus incidental learning paradox in episodic long-term memory.Journal of Experimental Psychology: General, 152(1):268, 2023

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.948579Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:18669b85f221ac34ec20e13fddfed3787893d87c4cfe8a0c39150c87d1942492

Observation 45c5423e-0e95-4453-bef4-17a3e3a6ab20 · outbound

This paper cites Generalized outcome-based strategy classification: Comparing deterministic and probabilistic choice models.Psychonomic bulletin & review, 21(6):1431–1443, 2014.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Generalized outcome-based strategy classification: Comparing deterministic and probabilistic choice models.Psychonomic bulletin & review, 21(6):1431–1443, 2014

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.148244Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:34a4ef3bd0bb663b79c5277eb3d5f2d98c182c4402fe7513750f05a4032d4768

Observation ffd6f9d9-9b8f-424d-9c8e-16d139cb9fe7 · outbound

This paper cites Deficits in category learning in older adults: Rule-based versus clustering accounts.Psychology and Aging, 32(5):473, 2017.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Deficits in category learning in older adults: Rule-based versus clustering accounts.Psychology and Aging, 32(5):473, 2017

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.106475Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:b86a3e24691032e248ec6984d06db8077ce207a612ffbab1f1827a686536b76e

Observation 335825fb-9a98-44a9-b179-e20910682f2d · outbound

This paper cites The globalizability of temporal discounting.Nature Human Behaviour, 6(10):1386–1397, 2022.

NeuroCogMap Reveals Cognitive Organization of Large Language Models The globalizability of temporal discounting.Nature Human Behaviour, 6(10):1386–1397, 2022

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.108307Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:dd2620817dc45b65c3041dff0d5ad816deb991926f07855fd915ad5e0b51a967

Observation 5d8a0687-3bf9-4e3d-889e-3ef194744dcf · outbound

This paper cites arm bandit task dataset (2022).URL osf.

NeuroCogMap Reveals Cognitive Organization of Large Language Models arm bandit task dataset (2022).URL osf

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.104682Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:bb90c5be845e30326b04e5805e8dd3a97d8fcf379ca488b33507b3773ea5492e

Observation 49659250-1f51-40e3-9694-b3222bff4b4b · outbound

This paper cites A new look at the statistical model identification.IEEE transactions on automatic control, 19(6):716–723, 1974.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A new look at the statistical model identification.IEEE transactions on automatic control, 19(6):716–723, 1974

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.241664Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:674109c95fcb6462b90e505aab571d9a2097d090271ac10b9734f6f7f84073b0

Observation c2fd8b5e-33b4-4e05-940f-af98f5dada4b · outbound

This paper cites Survey of hallucination in natural language generation.ACM computing surveys, 55(12):1–38.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Survey of hallucination in natural language generation.ACM computing surveys, 55(12):1–38

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.972047Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:cb8e44d0dc86c928d101ed55b846985fd4d10c51f0d37db1f53f5489ce00640a

Observation ece45297-43b2-4b4b-a74d-cda194d63750 · outbound

This paper cites Bias and fairness in large language models: A survey.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Bias and fairness in large language models: A survey

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.089281Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:66b6d8bce66717c7b69c22419b6dd53d93e6db1b2a8b2107bc6ef29c42287089

Observation 84db4d5d-91ef-4d1b-8e51-a083922b7870 · outbound

This paper cites Defending chatgpt against jailbreak attack via self-reminders.Nature Machine Intelligence, 5(12):1486– 1496, 2023.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Defending chatgpt against jailbreak attack via self-reminders.Nature Machine Intelligence, 5(12):1486– 1496, 2023

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.970173Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:1b9c5267f4fc5dcb3f8f0fd38c49d13c0d455db7c99de6fab9d3606f4ea62a10

Observation 3330bb36-3a51-407d-be25-1401fd1c7a7e · outbound

This paper cites Sycophantic ai decreases prosocial intentions and promotes dependence.Science, 391(6792):eaec8352, 2026.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Sycophantic ai decreases prosocial intentions and promotes dependence.Science, 391(6792):eaec8352, 2026

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.950497Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:eadc9207a9b429ddea89a77d42867dc6122f4f19367b75f97935f35eb11d8f0c

Observation 792b0aaf-ade6-4855-a129-efada7957649 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Attention is all you need.Advances in neural information processing systems, 30

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.987247Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:2a1c082266ffc368dce703867aa3f79d636763c3dc38f62b85ee8ddf1507ba18

Observation c2e0c98a-dd8c-457d-a0cd-66ff3ec580d5 · outbound

This paper cites Poldrack, Aniket Kittur, Donald Kalar, Eric Miller, Christian Seppa, Yolanda Gil, Douglas S.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Poldrack, Aniket Kittur, Donald Kalar, Eric Miller, Christian Seppa, Yolanda Gil, Douglas S

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.001703Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:19d3c8c1cfeb059937233b9762a55806436a5c367fc4d29b00dad23cef5e3f86

Observation 2c13e071-fab0-4cb4-a853-fd3767caa169 · outbound

This paper cites Poldrack, Thomas E.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Poldrack, Thomas E

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.964174Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:3bdf412dc2f8983c66842c4c131fd333535d5ec1cc3c294f8f0c2fbb4331b053

Observation e322485a-b52e-4bf3-ba30-108d0e36f26a · outbound

This paper cites Intent matters: Resolving the intentional versus incidental learning paradox in episodic long-term memory.Journal of experimental psychology.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Intent matters: Resolving the intentional versus incidental learning paradox in episodic long-term memory.Journal of experimental psychology

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.016763Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:9f5e5a70af5efd8631aaf4c3f90cec7f235aaa2ef5370b4cb959ef5fd39baafa

Observation f5c2ad99-0baf-4e18-99e3-610901659d95 · outbound

This paper cites A survey on multimodal large language models.National Science Review, 11(12):nwae403.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A survey on multimodal large language models.National Science Review, 11(12):nwae403

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.248860Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:53b70678b1ec57ed1d9d922447077a77d97710084b151c770fc7e1438629bdfc

Observation f16e3388-8111-4954-84fd-010f4bd05d54 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.008188Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:9a61039986d792783b1b6ef91e55e328e70ccfab613e8f5bf0f8b3d2425435bc

Observation bcad6693-cdf3-4fd3-bcc8-084f00994b50 · outbound

This paper cites Multimodal learning with next-token prediction for large multimodal models.Nature, pages 1–7, 2026.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Multimodal learning with next-token prediction for large multimodal models.Nature, pages 1–7, 2026

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.003752Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:8acd5323b9d13494f524b2827773995671ff4242620962fe2e8b6ee3133172bb

Observation fa55aa23-ee98-4db4-9db9-5eaafdff4846 · outbound

This paper cites A brain-wide map of neural activity during complex behaviour.Nature, 645:177–191, 2025.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A brain-wide map of neural activity during complex behaviour.Nature, 645:177–191, 2025

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.031322Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:dd0f18199721d941cdbda265a1cac6756951f587d9d23dc81c79d55da018c94b

Observation bcb4508d-4cd8-4311-98a5-f0c78d2b391f · outbound

This paper cites Greaves, Leonardo Novelli, Sina Mansour L., Andrew Zalesky, and Adeel Razi.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Greaves, Leonardo Novelli, Sina Mansour L., Andrew Zalesky, and Adeel Razi

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.071764Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:5932935a9ed3c44a6e9815e5fa82b6527eac1973795123217347ccc56be7687e

Observation 52f8dad9-399a-4ee6-a210-d8fd1168e519 · outbound

This paper cites Revealing gene function with statistical inference at single-cell resolution.Nature Reviews Genetics, 25:623–638, 2024.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Revealing gene function with statistical inference at single-cell resolution.Nature Reviews Genetics, 25:623–638, 2024

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.083490Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:2e4431ea0830ae71604433aff585c2741cf20d18a757d46afbe31282c1230c92

Observation b3a14216-c2f8-4a3e-a0c9-80701daf21e6 · outbound

This paper cites Openreview, 2026.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Openreview, 2026

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.128229Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:6528d5ae6fa4cd488366981b181ba78e8df3612ce9a109adf58c5647d9bf1583

Observation 88194d69-50b9-4d5e-b068-383929996362 · outbound

This paper cites Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders

Reference 83

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T02:46:27.620414Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:566cd524075135e60eec04970b61b6173e8d1f39bac35fddd3c99d6bc89b7608

Observation d7fcbd22-5479-42f7-b4aa-f1b7ec6ed35a · outbound

This paper cites Estimating the number of clusters in a data set via the gap statistic.Journal of the royal statistical society: series b (statistical methodology), 63(2):411– 423, 2001.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Estimating the number of clusters in a data set via the gap statistic.Journal of the royal statistical society: series b (statistical methodology), 63(2):411– 423, 2001

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.193769Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:6f8b724061ffaa4d810dd9f18126d7c464ae55903cff85ed094039acd790bf33

Observation e1b4bf55-2be7-4e45-9f89-14a7813a6eeb · outbound

This paper cites Human brain structural connectivity matrices–ready for modelling.Scientific Data, 9(1):486, 2022.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Human brain structural connectivity matrices–ready for modelling.Scientific Data, 9(1):486, 2022

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.994370Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:ee2d3f54dc402fe848e3c31ed52f1beb9633b43022177a7d8f7e4ac7e8d52ff2

Observation 4200c816-a518-4158-bf78-998410a6d6de · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

NeuroCogMap Reveals Cognitive Organization of Large Language Models gpt-oss-120b & gpt-oss-20b Model Card

Reference 86

Resolution
verified exact
local_arxiv, observed 2026-07-02T02:46:27.630089Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:1ac0c98c47bd0799fb1c02193fc19b1115754522073bf9882a2858c327ba0bba

Observation cf0e9154-ee76-4be3-a6d0-09f77974abff · outbound

This paper cites Update to GPT-5 system card: GPT-5.2.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Update to GPT-5 system card: GPT-5.2

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.946280Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:90682aed9e4968197471d4ebc24e4ccf659537411016ad0da0a0c127977df900

Observation c6d6ecdf-6e36-41ee-b189-a55aae96063a · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Efficient memory management for large language model serving with pagedattention

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.069867Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:5c0a5e6bbab610a15ebb628826e495845a859296935a797786609065f09930ec

Observation f8c0b2dd-1cdd-47a6-a091-42a338483609 · outbound

This paper cites Physics of language models: Part 3.1, knowledge storage and extraction.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Physics of language models: Part 3.1, knowledge storage and extraction

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.218519Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:dc7cc27a69c0b7d6cc7ad7d93a667e96c343b301b7570846d2fbdcddf9fd55b9

Observation d6020a4f-3810-4cad-be20-1a2d072a32d1 · outbound

This paper cites Decoupled weight decay regularization.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Decoupled weight decay regularization

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.230073Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:e1abeab57419dd31a19d9950b8e63abc06189340a56c40c23ad5c8aa2889f5f6

Observation 21dd0c5e-be95-4599-ac6a-5ad011782b02 · outbound

This paper cites Bbq: A hand-built bias benchmark for question answering.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Bbq: A hand-built bias benchmark for question answering

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.203354Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:e32c70b4a5c6b000fbf9cdbc57acf05cdbcd1f863fa3174d0213e853068c08d2

Observation b00e93ba-fc2b-4c7e-9085-9b15e7cc30c7 · outbound

This paper cites Towards understanding sycophancy in language models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Towards understanding sycophancy in language models

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.226419Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:87a1698f9ceb33a1b0ec4efa2bab66b766c91009c867797891fe3886f71cf5d5

Observation 3e09a797-f73d-49b1-91a3-178c7302997a · outbound

This paper cites A theory of pavlovian conditioning: Variations in the effectiveness of reinforcement and non-reinforcement.Classical conditioning, Current research and theory, 2:64–69, 1972.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A theory of pavlovian conditioning: Variations in the effectiveness of reinforcement and non-reinforcement.Classical conditioning, Current research and theory, 2:64–69, 1972

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.101157Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:3399b10c4980a7a5744f00904724e11aedf01bec8542b593b4666e6483300b0e

Observation a4ff0c29-0542-4b6e-b225-15fd3ca1efe7 · outbound

This paper cites A simple sequentially rejective multiple test procedure.Scandinavian journal of statistics, pages 65–70, 1979.

NeuroCogMap Reveals Cognitive Organization of Large Language Models A simple sequentially rejective multiple test procedure.Scandinavian journal of statistics, pages 65–70, 1979

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.126428Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:92cf9a0af715eda0d7b6be298e723e13ffb53f032bbc30079b37386468c038e5

Observation 26b5623d-9009-4600-9c53-c6bee1d4c8a8 · outbound

This paper cites an unresolved cited work.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Unresolved cited work

Reference 95

Resolution
unresolved
raw_fallback, observed 2026-07-06T09:02:13.073708Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:693faea543d1737d73dafbf1da9f260a21eab9858e111cc9e95b4c079bee4c71

Observation 2a7149a2-19c4-48d7-9811-10a3e4097e3a · outbound

This paper cites Measuring sycophancy of language models in multi-turn dialogues.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Measuring sycophancy of language models in multi-turn dialogues

Reference 96

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:46:27.611091Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:530bbb0d8ae943dedf69b2ff9ebdae673ebe0a1e4bc5bd8887743f7b6be702e5

Observation ef52fa1e-ec8f-478b-9efe-e4d4b25bdf80 · outbound

This paper cites Stereoset: Measuring stereotypical bias in pretrained language models.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Stereoset: Measuring stereotypical bias in pretrained language models

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:12.958116Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:1d3bfdbc1c21c169d9d268ed9fd542ddd943e812b3121007763f22a41f121f14

Observation 4fdebde6-2951-4e8a-a29b-c9d42c1fc492 · outbound

This paper cites Bias a-head? analyzing bias in transformer-based language model attention heads.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Bias a-head? analyzing bias in transformer-based language model attention heads

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.195616Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:244249a089277f79f27393c1d95af08073a2ec26b9485877485e431c388c2fdd

Observation 76aba3d2-22a6-4d33-ab9e-db05e36a7444 · outbound

This paper cites Monitoring latent world states in language models with propositional probes.

NeuroCogMap Reveals Cognitive Organization of Large Language Models Monitoring latent world states in language models with propositional probes

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.160017Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:ba9fff190528ef33959840fe1f378d8997379d0e41b26835c9a4a87320604063

Observation 79e8eb0b-519f-46c8-878a-19cbe792d4a4 · outbound

This paper cites The finley affair: A signal event in the history of forecast verification.Weather and forecasting, 11(1):3–20, 1996.

NeuroCogMap Reveals Cognitive Organization of Large Language Models The finley affair: A signal event in the history of forecast verification.Weather and forecasting, 11(1):3–20, 1996

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T09:02:13.163602Z

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.

source=pdf_text observed=2026-07-02T02:36:32.233113Z digest=sha256:10e3e89c1a5db80e05fd23a304676d847582b7a42ba6aaa694aae1ab40eba8e2

Pith citing papers

No inbound Pith citation observations are available.