Paper Citation Record · LEDGER

Geospatial Mechanistic Interpretability of Large Language Models

As of 16 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 2 inbound Pith citation observations for arXiv:2505.03368.

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

pith.paper-citation-record.v1
2505.03368 v2

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:56:32.651445Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T05:04:14.532933Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:04:37.217942Z

Reference resolution

74 of 74 outbound references displayed

verified exact2
verified fuzzy53
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40e2db96-7af6-46af-ad5b-2bad5898c97b · outbound

This paper cites On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper).

Geospatial Mechanistic Interpretability of Large Language Models On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.644110Z

Source-reported events for the cited work

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Observation 97fd03a8-557b-440d-9500-e99ccdb84ebf · outbound

This paper cites GPT, large language models (LLMs) and generative artificial intelligence (GAI) models in geospatial science: a systematic review.

Geospatial Mechanistic Interpretability of Large Language Models GPT, large language models (LLMs) and generative artificial intelligence (GAI) models in geospatial science: a systematic review

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.631311Z

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Observation 834c000f-38dc-460f-bb36-9a4de47b4efd · outbound

This paper cites Correctness Comparison of ChatGPT-4, Gemini, Claude-3, and Copilot for Spatial Tasks.

Geospatial Mechanistic Interpretability of Large Language Models Correctness Comparison of ChatGPT-4, Gemini, Claude-3, and Copilot for Spatial Tasks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.618746Z

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Observation b9a7e112-0d2a-4127-8693-06fb4f504140 · outbound

This paper cites Evaluating Large Language Models on Spatial Tasks: A Multi-Task Benchmarking Study.

Geospatial Mechanistic Interpretability of Large Language Models Evaluating Large Language Models on Spatial Tasks: A Multi-Task Benchmarking Study

Reference 4

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Source-reported events for the cited work

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Observation efc64125-888e-4f3f-a9e2-08e2b4294b78 · outbound

This paper cites Dialectical language model evaluation: An initial appraisal of the commonsense spatial reasoning abilities of LLMs.

Geospatial Mechanistic Interpretability of Large Language Models Dialectical language model evaluation: An initial appraisal of the commonsense spatial reasoning abilities of LLMs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.368266Z

Source-reported events for the cited work

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Observation ec9270d9-a459-48dd-85c3-d88b9d70d922 · outbound

This paper cites Evaluating the Ability of Large Language Models to Reason About Cardinal Directions.

Geospatial Mechanistic Interpretability of Large Language Models Evaluating the Ability of Large Language Models to Reason About Cardinal Directions

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.606087Z

Source-reported events for the cited work

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Observation fb50838b-7568-4377-b12e-5d7c2b1decda · outbound

This paper cites Advancing spatial reasoning in large language models: an in-depth evalu- ation and enhancement using the StepGame benchmark.

Geospatial Mechanistic Interpretability of Large Language Models Advancing spatial reasoning in large language models: an in-depth evalu- ation and enhancement using the StepGame benchmark

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.593331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 80ecd9f1-50eb-4d4d-802c-5469bec1535f · outbound

This paper cites Toponym resolution leveraging lightweight and open-source large language models and geo-knowledge.

Geospatial Mechanistic Interpretability of Large Language Models Toponym resolution leveraging lightweight and open-source large language models and geo-knowledge

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.581302Z

Source-reported events for the cited work

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Observation f48a692c-5956-4c0b-9125-557e4cf170f4 · outbound

This paper cites Autonomous GIS: the next-generation AI-powered GIS.

Geospatial Mechanistic Interpretability of Large Language Models Autonomous GIS: the next-generation AI-powered GIS

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.568917Z

Source-reported events for the cited work

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Observation 0a45537d-ec90-41db-b9b8-3a0b75181a0f · outbound

This paper cites GeoGPT: An assistant for understanding and processing geospatial tasks.

Geospatial Mechanistic Interpretability of Large Language Models GeoGPT: An assistant for understanding and processing geospatial tasks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.556607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 77441c62-e167-41ad-816d-a8f5133acdc1 · outbound

This paper cites BB-GeoGPT: A framework for learning a large language model for geographic information science.

Geospatial Mechanistic Interpretability of Large Language Models BB-GeoGPT: A framework for learning a large language model for geographic information science

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.544159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 78eb5acd-8736-42cb-8613-110502fbc3ca · outbound

This paper cites MapGPT: an autonomous framework for mapping by integrating large language model and cartographic tools.

Geospatial Mechanistic Interpretability of Large Language Models MapGPT: an autonomous framework for mapping by integrating large language model and cartographic tools

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.530699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5817dd03-dc16-4ab0-9029-7103377b314c · outbound

This paper cites GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilots.

Geospatial Mechanistic Interpretability of Large Language Models GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilots

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.517422Z

Source-reported events for the cited work

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Observation 1cdbde2b-eeb1-43ba-945c-3778135c654c · outbound

This paper cites On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications.

Geospatial Mechanistic Interpretability of Large Language Models On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.504323Z

Source-reported events for the cited work

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Observation 605a7bc0-300d-42bd-8933-9d8ac5893818 · outbound

This paper cites PlanGPT: Enhancing Urban Planning with Tailored Language Model and Efficient Retrieval.

Geospatial Mechanistic Interpretability of Large Language Models PlanGPT: Enhancing Urban Planning with Tailored Language Model and Efficient Retrieval

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.412213Z

Source-reported events for the cited work

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Observation 31860114-2030-4f8d-937a-d3d910fa1117 · outbound

This paper cites Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages.

Geospatial Mechanistic Interpretability of Large Language Models Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.490469Z

Source-reported events for the cited work

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Observation db22ae87-9f12-4e27-a7d0-67b9becdc7c2 · outbound

This paper cites Charting New Territories: Exploring the Geo- graphic and Geospatial Capabilities of Multimodal LLMs.

Geospatial Mechanistic Interpretability of Large Language Models Charting New Territories: Exploring the Geo- graphic and Geospatial Capabilities of Multimodal LLMs

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.477661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ad1e170c-c30d-45cc-98ea-1f0e1396b3c0 · outbound

This paper cites CityGPT: Empowering Urban Spatial Cognition of Large Language Models.

Geospatial Mechanistic Interpretability of Large Language Models CityGPT: Empowering Urban Spatial Cognition of Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.424319Z

Source-reported events for the cited work

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Observation d8a6780b-813a-47ca-b576-23dc2ee1a11f · outbound

This paper cites Distortions in Judged Spatial Relations in Large Language Models.

Geospatial Mechanistic Interpretability of Large Language Models Distortions in Judged Spatial Relations in Large Language Models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.464674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5d00706e-0e96-48ec-8223-7e32768bf59a · outbound

This paper cites Where to move next: Zero-shot generalization of llms for next poi recommendation.

Geospatial Mechanistic Interpretability of Large Language Models Where to move next: Zero-shot generalization of llms for next poi recommendation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.451171Z

Source-reported events for the cited work

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Observation 7309e001-c286-4611-8bbf-a449e25e3b4c · outbound

This paper cites Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text?.

Geospatial Mechanistic Interpretability of Large Language Models Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text?

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:56:32.867257Z

Source-reported events for the cited work

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Observation 8ae12ef7-6b1b-4342-ab4b-91cd8e0c99a8 · outbound

This paper cites GPT4GEO: How a Language Model Sees the World's Geography.

Geospatial Mechanistic Interpretability of Large Language Models GPT4GEO: How a Language Model Sees the World's Geography

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.440932Z

Source-reported events for the cited work

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Observation f4f86f76-0dcd-4d84-8dbb-458bfe74df2e · outbound

This paper cites Are Large Language Models Geospatially Knowledgeable? In: Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems.

Geospatial Mechanistic Interpretability of Large Language Models Are Large Language Models Geospatially Knowledgeable? In: Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.436830Z

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Observation 92350910-d30a-4769-93fa-30f562c5a7d5 · outbound

This paper cites Evaluation of Geographical Dis- tortions in Language Models: A Crucial Step Towards Equitable Representations.

Geospatial Mechanistic Interpretability of Large Language Models Evaluation of Geographical Dis- tortions in Language Models: A Crucial Step Towards Equitable Representations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.424120Z

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Observation cb0c3616-b91f-410f-ac07-ef98badc6010 · outbound

This paper cites Measuring Geographic Diversity of Foundation Models with a Natural Language–based Geo-guessing Experiment on GPT-4.

Geospatial Mechanistic Interpretability of Large Language Models Measuring Geographic Diversity of Foundation Models with a Natural Language–based Geo-guessing Experiment on GPT-4

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.411080Z

Source-reported events for the cited work

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Observation 73c961a3-86fe-4193-89a7-dc810962efd7 · outbound

This paper cites Making Geographic Space Explicit In Probing Multimodal Large Lan- guage Models For Cul-Tural Subjects.

Geospatial Mechanistic Interpretability of Large Language Models Making Geographic Space Explicit In Probing Multimodal Large Lan- guage Models For Cul-Tural Subjects

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.398078Z

Source-reported events for the cited work

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Observation af451028-fe89-42f6-8efd-ae6c60fe58f6 · outbound

This paper cites Mapping Great Britain’s semantic footprints through a large language model analysis of Reddit comments.

Geospatial Mechanistic Interpretability of Large Language Models Mapping Great Britain’s semantic footprints through a large language model analysis of Reddit comments

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.384974Z

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Observation a5591896-43de-4726-ac59-974a2ef8331d · outbound

This paper cites Deep learning.

Geospatial Mechanistic Interpretability of Large Language Models Deep learning

Reference 28

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Observation 097c4ce3-b092-48ff-b2e0-ff4b17226b22 · outbound

This paper cites Rectified linear units improve restricted boltzmann machines.

Geospatial Mechanistic Interpretability of Large Language Models Rectified linear units improve restricted boltzmann machines

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.363977Z

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Observation b9ce0fb3-773d-4da3-9126-8c75f0be51d8 · outbound

This paper cites Attention is All you Need.

Geospatial Mechanistic Interpretability of Large Language Models Attention is All you Need

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.351398Z

Source-reported events for the cited work

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Observation 420b0fe8-820c-45cc-8c99-52f898b76afa · outbound

This paper cites Representation Learning: A Review and New Perspectives.

Geospatial Mechanistic Interpretability of Large Language Models Representation Learning: A Review and New Perspectives

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.338218Z

Source-reported events for the cited work

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Observation a57c5d4b-ae99-48f7-95dc-9ed2d5645be0 · outbound

This paper cites Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet.

Geospatial Mechanistic Interpretability of Large Language Models Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.324488Z

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Observation d0d243d9-e02b-456c-a50f-363c62180eed · outbound

This paper cites Backpropagation and the brain.

Geospatial Mechanistic Interpretability of Large Language Models Backpropagation and the brain

Reference 33

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Observation bbf7c402-c772-4c5e-8b28-4a1d8949928c · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Geospatial Mechanistic Interpretability of Large Language Models Fine-Tuning Language Models from Human Preferences

Reference 34

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Observation c46bcb23-250b-404c-9c12-59b100402343 · outbound

This paper cites A Computer Movie Simulating Urban Growth in the Detroit Region.

Geospatial Mechanistic Interpretability of Large Language Models A Computer Movie Simulating Urban Growth in the Detroit Region

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.299134Z

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Observation 444d3a90-1bbf-409e-b011-eaa77ea0733b · outbound

This paper cites Do Language Models Know the Way to Rome? arXiv preprint arXiv:210907971.

Geospatial Mechanistic Interpretability of Large Language Models Do Language Models Know the Way to Rome? arXiv preprint arXiv:210907971

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.285864Z

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Observation b2d3b69e-5d56-427f-a034-5c39ea6f3356 · outbound

This paper cites Language Models Represent Space and Time.

Geospatial Mechanistic Interpretability of Large Language Models Language Models Represent Space and Time

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.273518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bdd79814-0708-4ee0-953b-765281beff33 · outbound

This paper cites On the Scaling Laws of Geographical Representation in Language Models.

Geospatial Mechanistic Interpretability of Large Language Models On the Scaling Laws of Geographical Representation in Language Models

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.260796Z

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Observation abbeb69e-e3dc-47df-8041-d08334b2db6f · outbound

This paper cites More than Correlation: Do Large Language Models Learn Causal Representations of Space?.

Geospatial Mechanistic Interpretability of Large Language Models More than Correlation: Do Large Language Models Learn Causal Representations of Space?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.512370Z

Source-reported events for the cited work

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Observation 5bf69930-c1a5-4fb3-be04-e48932751865 · outbound

This paper cites Geographic information analysis.

Geospatial Mechanistic Interpretability of Large Language Models Geographic information analysis

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.247627Z

Source-reported events for the cited work

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Observation b8f49b2a-32db-425d-a3a5-daada5aa8983 · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

Geospatial Mechanistic Interpretability of Large Language Models Mechanistic Interpretability for AI Safety -- A Review

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.520903Z

Source-reported events for the cited work

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Observation 3046608e-50d8-4721-a2cd-e9ed354a2c16 · outbound

This paper cites Investigating causal understanding in LLMs.

Geospatial Mechanistic Interpretability of Large Language Models Investigating causal understanding in LLMs

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.234232Z

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Observation bfa74f41-9456-42a3-8b32-7489b5eb4ec5 · outbound

This paper cites Do NLP models know numbers? probing numeracy in embeddings.

Geospatial Mechanistic Interpretability of Large Language Models Do NLP models know numbers? probing numeracy in embeddings

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.220334Z

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Observation d5c3ee01-cf28-456c-84f0-c9bb3fec58b1 · outbound

This paper cites Probing what different NLP tasks teach machines about function word comprehension.

Geospatial Mechanistic Interpretability of Large Language Models Probing what different NLP tasks teach machines about function word comprehension

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.206909Z

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Observation c58da48c-d103-4078-9a1f-2e60a386682d · outbound

This paper cites Probing classifiers: Promises, shortcomings, and advances.

Geospatial Mechanistic Interpretability of Large Language Models Probing classifiers: Promises, shortcomings, and advances

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.193965Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5444cf32-2014-43ad-a2cb-e850316e0007 · outbound

This paper cites Discourse probing of pretrained language models.

Geospatial Mechanistic Interpretability of Large Language Models Discourse probing of pretrained language models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.180552Z

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Observation 1ab6b834-4e70-40c2-a59f-821045a0e015 · outbound

This paper cites Probing for constituency structure in neural language models.

Geospatial Mechanistic Interpretability of Large Language Models Probing for constituency structure in neural language models

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.167628Z

Source-reported events for the cited work

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Observation 6478bfd5-5151-4e0a-9d7a-2f0b31f2df16 · outbound

This paper cites From Pretraining Data to Language Models to Downstream Tasks: May 2025 Tracking the Trails of Political Biases Leading to Unfair NLP Models.

Geospatial Mechanistic Interpretability of Large Language Models From Pretraining Data to Language Models to Downstream Tasks: May 2025 Tracking the Trails of Political Biases Leading to Unfair NLP Models

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.154249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ca216602-4557-4990-8cfe-11de467896e3 · outbound

This paper cites Probing pretrained language models for lex- ical semantics.

Geospatial Mechanistic Interpretability of Large Language Models Probing pretrained language models for lex- ical semantics

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.139975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b5b5e965-a8a5-4287-925d-53dc5555dc5f · outbound

This paper cites Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models.

Geospatial Mechanistic Interpretability of Large Language Models Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:56:32.794992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0b30eb07-38cb-49a3-bb38-870318d885d4 · outbound

This paper cites Identifying Linear Relational Concepts in Large Language Models.

Geospatial Mechanistic Interpretability of Large Language Models Identifying Linear Relational Concepts in Large Language Models

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.127594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6aeb3cb4-6433-4aba-bba4-cf4d8f907974 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Geospatial Mechanistic Interpretability of Large Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.114699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2d59b6b7-40a0-43fb-b9b4-6d107f09b705 · outbound

This paper cites Spatial autocorrelation.

Geospatial Mechanistic Interpretability of Large Language Models Spatial autocorrelation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.101290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 64bf12f7-3ff2-4515-996c-1c3813b7ac2d · outbound

This paper cites A quantitative analysis of global gazetteers: Patterns of coverage for common feature types.

Geospatial Mechanistic Interpretability of Large Language Models A quantitative analysis of global gazetteers: Patterns of coverage for common feature types

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.088797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fa648df7-8a6b-43f6-ad56-61472fb55d89 · outbound

This paper cites Mistral 7B.

Geospatial Mechanistic Interpretability of Large Language Models Mistral 7B

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.581388Z

Source-reported events for the cited work

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Observation f157cf26-6ceb-4f52-98ef-74c04cf129e2 · outbound

This paper cites Training language mod- els to follow instructions with human feedback.

Geospatial Mechanistic Interpretability of Large Language Models Training language mod- els to follow instructions with human feedback

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.067214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 691a7602-d3f1-49a4-a068-4e0da0dc08cf · outbound

This paper cites Toy Models of Superposition.

Geospatial Mechanistic Interpretability of Large Language Models Toy Models of Superposition

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.053876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 623df2d3-dad1-48d0-9c8c-e41bb5013daf · outbound

This paper cites Pooling methods in deep neural networks, a review.

Geospatial Mechanistic Interpretability of Large Language Models Pooling methods in deep neural networks, a review

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.040232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ce8763dd-764b-46bb-9292-320f0e21de81 · outbound

This paper cites Notes on Continuous Stochastic Phenomena.

Geospatial Mechanistic Interpretability of Large Language Models Notes on Continuous Stochastic Phenomena

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.026671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 66fb3361-14e3-499e-925d-6f5629528c53 · outbound

This paper cites Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs.

Geospatial Mechanistic Interpretability of Large Language Models Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:33.012675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 07a83027-504e-4f05-b515-90d82868cf30 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Geospatial Mechanistic Interpretability of Large Language Models Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.614434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b67fb82-482b-450b-9dd3-e840330694e3 · outbound

This paper cites Towards Monosemantic- ity: Decomposing Language Models With Dictionary Learning.

Geospatial Mechanistic Interpretability of Large Language Models Towards Monosemantic- ity: Decomposing Language Models With Dictionary Learning

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:32.998708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dbeaddd1-00eb-4a20-8607-88072b28a106 · outbound

This paper cites Sparse autoencoder.

Geospatial Mechanistic Interpretability of Large Language Models Sparse autoencoder

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:32.985580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 79f42052-dbc4-4d56-8221-5014e3c13e4b · outbound

This paper cites Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs.

Geospatial Mechanistic Interpretability of Large Language Models Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.610262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ff95358-5592-41f9-a8da-68be2a921924 · outbound

This paper cites Open Problems in Mechanistic Interpretability.

Geospatial Mechanistic Interpretability of Large Language Models Open Problems in Mechanistic Interpretability

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.630622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87c856a5-1213-4f27-a86a-07cdad87f7a6 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Geospatial Mechanistic Interpretability of Large Language Models On the Opportunities and Risks of Foundation Models

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.634696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c79c933b-438b-46b8-893e-221595ceae3f · outbound

This paper cites Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small; 2022.

Geospatial Mechanistic Interpretability of Large Language Models Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small; 2022

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:32.972197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 0999ebb9-7dd9-445f-865a-e7c5605d499f · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Geospatial Mechanistic Interpretability of Large Language Models Scaling and evaluating sparse autoencoders

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.625763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ace1060-9839-4252-b4ec-66c796fcca9e · outbound

This paper cites Modelling vague places with knowledge from the Web.

Geospatial Mechanistic Interpretability of Large Language Models Modelling vague places with knowledge from the Web

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:32.959334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 11d981d1-b90b-4d92-ab2a-7e6a8d8da285 · outbound

This paper cites GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond.

Geospatial Mechanistic Interpretability of Large Language Models GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:56:32.946053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9aaa1cab-5325-4587-8747-2307b6d0c267 · outbound

This paper cites Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models.

Geospatial Mechanistic Interpretability of Large Language Models Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.643523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6feec10b-7783-440d-a5bd-4726570dbbd3 · outbound

This paper cites Toy Models of Superposition.

Geospatial Mechanistic Interpretability of Large Language Models Toy Models of Superposition

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.593508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7eba744-9f3f-493b-aa64-562bbcd046af · outbound

This paper cites On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications.

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.408106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37259343-89bc-4d77-86f1-b3d382414c1e · outbound

This paper cites Identifying Linear Relational Concepts in Large Language Models.

Geospatial Mechanistic Interpretability of Large Language Models Identifying Linear Relational Concepts in Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T23:56:32.565506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 3f64e5d5-8ae5-44b7-a6d3-81ae1e23a9d0 · inbound

IoT-Brain: Grounding LLMs for Semantic-Spatial Sensor Scheduling cites this paper.

IoT-Brain: Grounding LLMs for Semantic-Spatial Sensor Scheduling Geospatial Mechanistic Interpretability of Large Language Models

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:05:56.775324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c2f62e79-5c90-4c42-891b-a33d6bec49b5 · inbound

Interaction Locality in Hierarchical Recursive Reasoning cites this paper.

Interaction Locality in Hierarchical Recursive Reasoning Geospatial Mechanistic Interpretability of Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:04:37.220267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.