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Paper Citation Record · LEDGER

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning

As of 8 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2507.19586.

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

pith.paper-citation-record.v1
2507.19586 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:20:39.572695Z

measured 59 of 59 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

59 of 59 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved57
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77287c61-2635-46a4-b3db-8d8aa34f1a1b · outbound

This paper cites LAMP: A Language Model on the Map.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning LAMP: A Language Model on the Map

Reference 1

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verified exact
local_arxiv, observed 2026-08-06T14:20:39.911690Z

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 46522376-5957-45b4-819b-23a9c2f09d8f · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 2

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no resolver link, observed 2026-08-06T14:20:37.043796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:37.043796Z digest=sha256:a94a3654b7aa8158a8ee43fb04dcb79580976d272ca43b2774c4949919a7004c

Observation 74aa8a65-a88f-4f57-9561-59f90caca0d5 · outbound

This paper cites Does your data spark joy? Performance gains from domain upsampling at the end of training.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Does your data spark joy? Performance gains from domain upsampling at the end of training

Reference 3

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no resolver link, observed 2026-08-06T14:20:37.130182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:37.130182Z digest=sha256:039aab861cb35c1fcbbbb28c62d952e3ea8185d2a91631747e46f349847da072

Observation 8537da3c-7809-477a-8298-19d517e2f138 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:20:40.133464Z

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=arxiv_source observed=2026-08-06T14:20:37.225927Z digest=sha256:2ed3832a1f4a62bd4dc423efdcc788d1518ee3d0adcc3b9cefbcf1c4b7717681

Observation 5daae739-3d7d-4480-8883-4a40c40b2c98 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 5

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raw_fallback, observed 2026-08-06T14:20:40.122886Z

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=arxiv_source observed=2026-08-06T14:20:37.332519Z digest=sha256:154ac7b4d4a792fdd89d945298c9510158b5f41e00a6a3691c296feff6083563

Observation cc1cbd8c-44a0-4f22-9bbf-36488e43bc18 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 6

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raw_fallback, observed 2026-08-06T14:20:40.112805Z

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=arxiv_source observed=2026-08-06T14:20:37.409992Z digest=sha256:8a9f6572a18e552f5e6b68de7e072f9c7b10802ffddb3a0686eda596984275c2

Observation 2731cb6d-99c4-4a62-8883-91c50887085a · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning KTO: Model Alignment as Prospect Theoretic Optimization

Reference 7

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no resolver link, observed 2026-08-06T14:20:37.513297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:37.513297Z digest=sha256:9c10e385fa2e741a06d8d54f6eaef334efd8689809104c4f5d3a8e43502675f7

Observation b9864230-f6c5-4a8f-aab5-199e1b666f02 · outbound

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

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning CityGPT: Empowering Urban Spatial Cognition of Large Language Models

Reference 8

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no resolver link, observed 2026-08-06T14:20:37.640195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:37.640195Z digest=sha256:301f1446800358834a92716ef900a23a24d45b81b5e222019812638c01da7657

Observation cc14f001-8a42-4134-a719-e2ff8ecbc41f · outbound

This paper cites AgentMove: A Large Language Model based Agentic Framework for Zero-shot Next Location Prediction.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning AgentMove: A Large Language Model based Agentic Framework for Zero-shot Next Location Prediction

Reference 9

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no resolver link, observed 2026-08-06T14:20:37.898366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:37.898366Z digest=sha256:4b436bea6080eba8cfd832feea3f2b6da3b0b049f37f4040c3da1044ab116f35

Observation 18c7aecb-95ba-45fc-959b-76006ad871ec · outbound

This paper cites CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning CityBench: Evaluating the Capabilities of Large Language Models for Urban Tasks

Reference 10

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no resolver link, observed 2026-08-06T14:20:38.111020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:38.111020Z digest=sha256:c61db9597ad51bd8d6b58c5bc81ce7731d5a31dd5841364becd7875387655580

Observation c0623356-ae1f-41c1-bad6-8f98389a36a3 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 11

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raw_fallback, observed 2026-08-06T14:20:40.103096Z

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 b15f4966-fa3c-4c37-b294-a3b7285515e8 · outbound

This paper cites Language Models Represent Space and Time.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Language Models Represent Space and Time

Reference 12

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no resolver link, observed 2026-08-06T14:20:38.431329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:38.431329Z digest=sha256:6dbd5c978d8422d96a44296b43fb008214a40cea8777ed8a73cbe6d26d45b1d8

Observation 3a473178-a00e-4c23-94cc-6e1ab520ba22 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Measuring Massive Multitask Language Understanding

Reference 13

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no resolver link, observed 2026-08-06T14:20:38.613110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:38.613110Z digest=sha256:b837d4e26d4d2e6f3d29af0622949a76ab7c5f7205cc229ff298814b42e09f58

Observation d7f8ef38-1b19-4e75-97c8-067d3084672a · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 14

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no resolver link, observed 2026-08-06T14:20:38.767274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:38.767274Z digest=sha256:f41b1ef404984dd88b3e06c30d8783daccae4796960cedf259668a324c433831

Observation 430b51c1-930d-4651-be7b-eb1c10eac77a · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 15

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no resolver link, observed 2026-08-06T14:20:38.948935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:38.948935Z digest=sha256:326763bf0de63c336fff191fe714546f75fc58126b1ec7562fd39909cf260cc4

Observation 3915d2a3-5b46-4043-b357-e52484e5dd18 · outbound

This paper cites Elements of World Knowledge (EWoK): A Cognition-Inspired Framework for Evaluating Basic World Knowledge in Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Elements of World Knowledge (EWoK): A Cognition-Inspired Framework for Evaluating Basic World Knowledge in Language Models

Reference 16

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no resolver link, observed 2026-08-06T14:20:39.123843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.123843Z digest=sha256:971cf26d336c8b86b3bbde1a6d42f2da3b950ed33b6bbe561523522546d9adb1

Observation 80ef9748-5f5b-4222-8458-bfd64c92dd7e · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 17

Resolution
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no resolver link, observed 2026-08-06T14:20:39.308234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.308234Z digest=sha256:e258eed6aa1ddf6259b0783a85650b9be1740d67ba31914e9b5c7d4dd4228306

Observation 6b25b2bd-cbf1-4853-86e2-42934e879a33 · outbound

This paper cites UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models

Reference 18

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no resolver link, observed 2026-08-06T14:20:39.442466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.442466Z digest=sha256:11de1dc8e837f4e25e49bf09dd53df2ff1006f7ebd453a13cd62f576c04fe0b7

Observation 7bd87858-0e17-4859-84b2-a67a8d1d210e · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 19

Resolution
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raw_fallback, observed 2026-08-06T14:20:40.081844Z

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=arxiv_source observed=2026-08-06T14:20:39.446228Z digest=sha256:e54cb7f45f2fa46b5f56a9682da8c5979b97b4ab2f73912ed15799e17a7b90bd

Observation 44ca190c-f2c5-4a35-a5ae-8dc505da24c5 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 20

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unresolved
raw_fallback, observed 2026-08-06T14:20:40.073455Z

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=arxiv_source observed=2026-08-06T14:20:39.449122Z digest=sha256:b96ba48d0d023e410340392c1dbded463221171e95171fc057a15cb9ac476b33

Observation 5408fed3-2ee3-4c9a-ac70-e7038324a0ad · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 21

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raw_fallback, observed 2026-08-06T14:20:40.064559Z

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=arxiv_source observed=2026-08-06T14:20:39.452669Z digest=sha256:a379b7dca143332f4409f51974d4136a2a9a57e7636d7758abb67a3064df5f03

Observation 5aa7e3de-3087-40b0-874e-203a6f7de0f7 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Gonzalez, Hao Zhang, and Ion Stoica

Reference 22

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no resolver link, observed 2026-08-06T14:20:39.455721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.455721Z digest=sha256:d38d71caa750ce13ae68a0c234fb62f12be5e557a0b0a5777c4797ec815cb9db

Observation fbe28c98-b388-4f57-b0b3-7d3e625f8f2e · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 23

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no resolver link, observed 2026-08-06T14:20:39.458620Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.458620Z digest=sha256:05f324b01f01c7f1203a9fdea568ab60208c71d7a7ac3e8e2accc80df34594fd

Observation 737cab4d-9dad-45f4-b279-1fb76a6dbedb · outbound

This paper cites u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \

Reference 24

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no resolver link, observed 2026-08-06T14:20:39.462027Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.462027Z digest=sha256:fc7c1d2c2c74a12b8598c7814d62747d2eca8bbacf6413b50f14e9b07c442e27

Observation d00d9c6a-360e-4dd2-8359-93c666cd0338 · outbound

This paper cites Leybzon and Corentin Kervadec.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Leybzon and Corentin Kervadec

Reference 25

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no resolver link, observed 2026-08-06T14:20:39.465444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.465444Z digest=sha256:1b8b18440a0e6d58c0c861b837dca209196130830a8638f9f3da57744c9cb090

Observation 00711774-f145-48f1-b97b-07caf98b913c · outbound

This paper cites HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models

Reference 26

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no resolver link, observed 2026-08-06T14:20:39.469184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.469184Z digest=sha256:d80cd35fbf599533c6c1ecf4688ed03b386e79f53ed61f8f04cf0f5296b956c1

Observation e953a4a6-2437-4633-a75c-ff85c19e4b7e · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 27

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verified exact
doi, observed 2026-08-06T14:20:39.617849Z

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=arxiv_source observed=2026-08-06T14:20:39.472419Z digest=sha256:3cf3b2ba9a66375ac6e6072690a5978c765d9ee754a47ade2aadbaa6e5184dda

Observation c563a84f-9d42-4090-9b16-954521c30fb8 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 28

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no resolver link, observed 2026-08-06T14:20:39.475564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.475564Z digest=sha256:ab78806ea034226d40e93607cdea2bf5324a960f3e3072d2619a587f031a449b

Observation 7e19f1d4-6164-4b84-af61-8193b01c4e2d · outbound

This paper cites G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment

Reference 29

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no resolver link, observed 2026-08-06T14:20:39.478226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.478226Z digest=sha256:9389a39fbb051a900b28af690c59e70da860a7752bbf490e6e7a9263cbef8697

Observation 938ebbcc-111e-4e82-b6e0-ab54fd7f5a6d · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 30

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raw_fallback, observed 2026-08-06T14:20:40.035998Z

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=arxiv_source observed=2026-08-06T14:20:39.481214Z digest=sha256:71b1bf46fe56b7b9370874ab871de208c903db94842607ac01f5ad31c6e58c3e

Observation b482d053-946f-4ed2-943d-1f36a8bfd590 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 31

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unresolved
raw_fallback, observed 2026-08-06T14:20:40.026534Z

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=arxiv_source observed=2026-08-06T14:20:39.484017Z digest=sha256:2aa841c75139ccbb31e4ac271f529680946caf116edd055b845af8eb140240a3

Observation 219be661-09d5-494f-a9d5-45116a37cbad · outbound

This paper cites SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 32

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no resolver link, observed 2026-08-06T14:20:39.486629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.486629Z digest=sha256:896d50ba34e9ba8533c9fb5b8d8a96f2ee9d5480032ef4a1f45d830ceb54d3f6

Observation 9e318d8a-5a4d-4f1f-8bd8-ee2b12cc9d1e · outbound

This paper cites Large Language Models are Geographically Biased.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Large Language Models are Geographically Biased

Reference 33

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no resolver link, observed 2026-08-06T14:20:39.489448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.489448Z digest=sha256:cb84878923b5299bc057ddd768c248b7acf9d3ef8eb33b254906ac4db5483f85

Observation 5bd645c0-cb67-4a04-a6ae-bdb8b142b805 · outbound

This paper cites GeoLLM: Extracting Geospatial Knowledge from Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning GeoLLM: Extracting Geospatial Knowledge from Large Language Models

Reference 34

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no resolver link, observed 2026-08-06T14:20:39.492659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.492659Z digest=sha256:9a67c0513f1f31ee35ae9b94a8a5e3a45c4130ff607133f05df670d189ac509c

Observation 8881e4ed-09c8-4112-a246-4ea352e418c1 · outbound

This paper cites On Faithfulness and Factuality in Abstractive Summarization.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning On Faithfulness and Factuality in Abstractive Summarization

Reference 35

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no resolver link, observed 2026-08-06T14:20:39.495718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.495718Z digest=sha256:6e1ce85bb6c0d5a0063a05ba59dbeb2da09c1474d98d8661f8c2c829900d15ef

Observation f47cdfd2-6ff3-47f4-920d-be62f684eb14 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 36

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unresolved
raw_fallback, observed 2026-08-06T14:20:40.017113Z

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 a1d16062-58b2-4f06-b6a4-c5099c076ea6 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-06T14:20:40.008320Z

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=arxiv_source observed=2026-08-06T14:20:39.501677Z digest=sha256:f86a955412e1c5cad84ab2f53f79b4741392e7c9f5daada01bb3de7aec1a5591

Observation 61ed2393-bcd8-4b02-a195-7c22b1dedf78 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:20:39.999091Z

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 edfe7cc7-b11d-4ca6-8c8b-12ed9af6667a · outbound

This paper cites Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Reference 39

Resolution
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no resolver link, observed 2026-08-06T14:20:39.507841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.507841Z digest=sha256:362db9e4cb3c623fa94fb1dcc2a40613728fe73832859f6c052eaf3a1a443d1d

Observation 56282499-2618-41fc-91a6-8a9e3e62041c · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.510919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.510919Z digest=sha256:c12f0b0bac5c66cfab429b6ea31fe1ad601a7b832e02d712bfd7e694a6be54d5

Observation ac72bf55-4c40-4b6e-b827-431e7bf1d918 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.513335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.513335Z digest=sha256:031a59d6a18f90d9d84241535d7dd76cc07799558984f0a0a0046b32de89a2ea

Observation f0326669-af90-4a98-8385-49be07e8d108 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:20:39.977614Z

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=arxiv_source observed=2026-08-06T14:20:39.516278Z digest=sha256:9b3e9a7c5d28af9ef47f22f88ba8ad09cf6a4103298f5edb59f86b42b95d2775

Observation 2339044d-154f-4438-9cbf-5f79049236e5 · outbound

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

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning GPT4GEO: How a Language Model Sees the World's Geography

Reference 43

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no resolver link, observed 2026-08-06T14:20:39.519135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.519135Z digest=sha256:6bf9f898bda2f9a0247fb0c3c2d1a3b154d6cd58f765ea65c21b6156ab8bd249

Observation f54270a9-b169-42da-9951-d69af2c40dc3 · outbound

This paper cites GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Framework.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Framework

Reference 44

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no resolver link, observed 2026-08-06T14:20:39.522889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation aa855f5a-0a76-415a-8faa-b75c29d8a6a0 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.526039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.526039Z digest=sha256:066e901b33c029a907d17fa6704f6b05a2b8d2521279e1d7647864604809af66

Observation 61b340c6-f583-4448-859e-003893c2ac7f · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.529498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.529498Z digest=sha256:44f407fe7fa4fcf8a011d2793dde2379ef10c42da2beddb7aab0419648b25ae6

Observation 5127f389-1dee-470c-868b-467f4c70ba8e · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:20:39.967907Z

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=arxiv_source observed=2026-08-06T14:20:39.532818Z digest=sha256:a7de040040f7dcfb1f401fe65830fa6bb123e0ad7e23b1f863afa1a0bda292af

Observation 37c28dd9-b82c-4100-b2c2-a8688f194841 · outbound

This paper cites Where Would I Go Next? Large Language Models as Human Mobility Predictors.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Where Would I Go Next? Large Language Models as Human Mobility Predictors

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.536466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.536466Z digest=sha256:7629aeebcdf2d3bb9380bcfa167c898a9f5f6b9fe52f6ba0d576cabb7a0ce1e0

Observation ac9b9f45-07ca-4e37-97db-7591659248b1 · outbound

This paper cites Emergent Abilities of Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Emergent Abilities of Large Language Models

Reference 49

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unresolved
no resolver link, observed 2026-08-06T14:20:39.540107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.540107Z digest=sha256:53e3ddef43b2956cf48fabe14b8c431b01957fc2a0663fd648936bc61b0ef8f4

Observation 832e6853-eb30-4227-9854-cbeee8f18e86 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:20:39.956880Z

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=arxiv_source observed=2026-08-06T14:20:39.544927Z digest=sha256:0a20945a5d2b34fa0fdda94349d5f41de2dfc295fd180e483d7bc347fc2934ec

Observation 1fdfaa2d-0333-462a-b814-0f5f42db532a · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:20:39.946290Z

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=arxiv_source observed=2026-08-06T14:20:39.548109Z digest=sha256:9b40d6660bef10f50cd498de3d2a64ca2257f0c9a39c40caaa195cdfd36e1124

Observation 2ddb05b2-8c71-416b-940c-12c159fd655c · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 52

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unresolved
no resolver link, observed 2026-08-06T14:20:39.550900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.550900Z digest=sha256:f5e2a0d67dc3bcf6ca970c564b57b1d68ef8161275dbfff59b70b5d1a7724343

Observation 7b80b004-7133-449e-a6de-2ef0082bc435 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:20:39.936185Z

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=arxiv_source observed=2026-08-06T14:20:39.553828Z digest=sha256:4a08e47ed9d75b2cb320633a06f9ad162129ca62ab27f22d2964da0528e75837

Observation 6ba141e8-bf0f-48e4-a078-544c10a7c976 · outbound

This paper cites KoLA: Carefully Benchmarking World Knowledge of Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning KoLA: Carefully Benchmarking World Knowledge of Large Language Models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.556719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.556719Z digest=sha256:db3f0d8b22cf876f34dd0780376a4dffe0ff03a12dd1219705e34063b79418ea

Observation b41a872f-1157-475a-9674-d073bc149717 · outbound

This paper cites an unresolved cited work.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Unresolved cited work

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.559792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.559792Z digest=sha256:31fb4998807aacc0bf0b8720eece6f842e16b841289da3662f91fae76da12e53

Observation 7ff01261-af4e-440e-8cfb-0af97897b876 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.562552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.562552Z digest=sha256:558dc87bb7e680153b64de373feae3e762fb8d54b17400ea1f604fe1023bd48f

Observation 7f365d0a-f520-4dce-8acd-ff15d911d534 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning Instruction-Following Evaluation for Large Language Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.565667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.565667Z digest=sha256:14ba1071b4c21ca17a815b729864e677b713537e09cce02c8612e4869fa60456

Observation 5f4d87bb-39de-4b88-ac5f-a4b15fb908de · outbound

This paper cites online" 'onlinestring :=.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning online" 'onlinestring :=

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.569004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.569004Z digest=sha256:cdff593dadb35e6e43ea5f0351df93c8ee37f1b179cc74af269e69edf0359405

Observation b40eb9f5-e6a3-4c20-a319-c7cf4716a16b · outbound

This paper cites write newline.

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning write newline

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T14:20:39.572695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:20:39.572695Z digest=sha256:b7fe248379d73792ab9839f64c29373947bbb8a4917d643951cdd823d6771fd9

Pith citing papers

No inbound Pith citation observations are available.