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Paper Citation Record · LEDGER

Beyond Facts: Evaluating Intent Hallucination in Large Language Models

As of 20 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.06539.

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

pith.paper-citation-record.v1
2506.06539 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:59:45.148904Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

33 of 33 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7486e26c-2f03-451b-b57d-fc3cdaf1ab93 · outbound

This paper cites The Internal State of an LLM Knows When It's Lying.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models The Internal State of an LLM Knows When It's Lying

Reference 1

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source=arxiv_source observed=2026-08-07T05:59:42.983678Z digest=sha256:feb76a71465c68e31396401bb12019534684b1eb5e3084331556c02a173518ad

Observation af59f1e0-b7bf-40b0-b518-e7dd09bc33fa · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 2

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doi, observed 2026-08-07T05:59:45.205301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T05:59:43.082483Z digest=sha256:cec750a6e7d2bd4eec7b133510bd29f234d593f09ec9d92114b703186f36cbd0

Observation 1dbc5d44-9024-428c-b333-cbc9696dcf43 · outbound

This paper cites Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization

Reference 3

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source=arxiv_source observed=2026-08-07T05:59:43.157123Z digest=sha256:72072648453f81746892b168af7dd36531de48a08b3f3b5627f85c68b2112cf4

Observation 813cdce5-ddb9-4dbc-b57a-58910839ddd6 · outbound

This paper cites FELM: Benchmarking Factuality Evaluation of Large Language Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models FELM: Benchmarking Factuality Evaluation of Large Language Models

Reference 4

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source=arxiv_source observed=2026-08-07T05:59:43.265833Z digest=sha256:2e824522f9863d4297b974427845335f6b243d86c4b31b2fc0d8be5fa005d027

Observation 499c3ed1-298b-4b73-94ea-c1839f07e23d · outbound

This paper cites The Llama 3 Herd of Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models The Llama 3 Herd of Models

Reference 5

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source=arxiv_source observed=2026-08-07T05:59:43.349807Z digest=sha256:354d3cc26dfa889cfbe47b827b473fa180b833ab9693f5ad0fbb73b937bf5dca

Observation 6e4690cb-73dd-4714-b550-5d69ac0a0a28 · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 6

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raw_fallback, observed 2026-08-07T05:59:45.489654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T05:59:43.437293Z digest=sha256:4067184a61ca86a2e82884fcf2f6f2a829ecc118d07343d81e5629d345fd5482

Observation 3f9ba1b7-4bfe-4f8a-9dcd-48e09c598241 · outbound

This paper cites A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation

Reference 7

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T05:59:43.526747Z digest=sha256:c6fd28d503124baba21a3996c13593cd5e0ffc8a7b3b4f28a43c4927e3b608aa

Observation d8fb3b0e-2f69-45e2-87a2-1b974f8a7ff3 · outbound

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

Beyond Facts: Evaluating Intent Hallucination in Large Language Models A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 8

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source=arxiv_source observed=2026-08-07T05:59:43.609322Z digest=sha256:2e69ca2ccf09cdb5b4c720b87de6bbc9c5b13d84062373033263ad84327ffef7

Observation 8df5f450-380c-4a56-9db7-3af207d7fac4 · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 9

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source=arxiv_source observed=2026-08-07T05:59:43.689890Z digest=sha256:7cebef9b6a8d8eecdd79a52f2fc568a9eccf41c799efebb0244990004a2c4f73

Observation 1a17cd4e-0354-45da-91eb-e25eb0a49620 · outbound

This paper cites Mistral 7B.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Mistral 7B

Reference 10

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source=arxiv_source observed=2026-08-07T05:59:43.753431Z digest=sha256:04d54aef5b631660b90286656e689dc6e8218d45bcb14ca2cc6e941ef5674080

Observation 5d24f450-98f6-456e-a2c3-66500b910799 · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 11

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c0594533-16f9-4a33-a6a3-fb39606e34e9 · outbound

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

Beyond Facts: Evaluating Intent Hallucination in Large Language Models HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models

Reference 12

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source=arxiv_source observed=2026-08-07T05:59:43.915918Z digest=sha256:2ad29a83b4571030c6c2d5b5fc2a0c69e9876ab20dd1bce3575590adb077e786

Observation 0da7d885-f47c-4439-8a21-4a6f2d24ae8b · outbound

This paper cites Lost in the Middle: How Language Models Use Long Contexts.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Lost in the Middle: How Language Models Use Long Contexts

Reference 13

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source=arxiv_source observed=2026-08-07T05:59:43.976991Z digest=sha256:0841ce47e26226abd8525ace29c0744afbfdd7b6dc6e1164c5522fa734a6cd2f

Observation 0222f3b5-73e5-4915-b6a1-0b85358da39b · outbound

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

Beyond Facts: Evaluating Intent Hallucination in Large Language Models SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 14

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source=arxiv_source observed=2026-08-07T05:59:44.062538Z digest=sha256:cc56e6b5c3dbcc26af051d94135c01b3260781b6d192fee9817f85d3adbeef57

Observation 5138a1cf-6e21-4d72-9246-c9e9298dabf4 · outbound

This paper cites FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

Reference 15

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source=arxiv_source observed=2026-08-07T05:59:44.143311Z digest=sha256:d14ddb1c76435c8aa9ee457ce13f5bf6250d6e2f48cc261c0957289bfc895a02

Observation 081ff96c-3773-4096-bb1d-ecc99865d9b1 · outbound

This paper cites FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows".

Beyond Facts: Evaluating Intent Hallucination in Large Language Models FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"

Reference 16

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source=arxiv_source observed=2026-08-07T05:59:44.232248Z digest=sha256:dc4e92c05c8cc63fc5b46540ec4d961a8533e3711cd9a51276c659baa659d930

Observation b6bb0d91-3f18-49f6-ae84-35f6e2313de8 · outbound

This paper cites Fine-grained Hallucination Detection and Editing for Language Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Fine-grained Hallucination Detection and Editing for Language Models

Reference 17

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source=arxiv_source observed=2026-08-07T05:59:44.316066Z digest=sha256:b67b0ff9f4d81805bcc15853d3bb0cfbaa8d9e512fcc06a88c84942a3053a2bd

Observation 68a25084-bb5a-4f50-ad2d-6a5e45d3ab3e · outbound

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

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Reference 18

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Observation 5bd0733c-425f-459f-a042-caaabb334476 · outbound

This paper cites RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models

Reference 19

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source=arxiv_source observed=2026-08-07T05:59:44.496379Z digest=sha256:71e14273c7d9cc1ae1b2398226ab390260c21f8a29ffdab41cc2a85fd4520eb8

Observation f4114e0e-2579-4684-8d30-7ed1de508f8c · outbound

This paper cites GPT-4 Technical Report.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models GPT-4 Technical Report

Reference 20

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source=arxiv_source observed=2026-08-07T05:59:44.596701Z digest=sha256:25726c648393c5750f8036422ad1b147bcff6b6f71a2d3797d4e2eb1c28089d4

Observation e5a595aa-45dd-4311-94fb-a2086e0d5151 · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0ffed680-fcb8-4413-9c16-0d51fb04d1fe · outbound

This paper cites InFoBench: Evaluating Instruction Following Ability in Large Language Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models InFoBench: Evaluating Instruction Following Ability in Large Language Models

Reference 22

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Observation 311cca00-19e7-49ed-bf4a-75059a34d13d · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 23

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source=arxiv_source observed=2026-08-07T05:59:44.636835Z digest=sha256:40ba8c8abfd179482d189b1d4a0e0fec0b3037ee970bc95e77e170934dbe74b4

Observation 7a078d58-06a7-4aa2-a52b-726e26932c19 · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 24

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d4105d1c-af86-41ff-8019-40790cbf07e6 · outbound

This paper cites an unresolved cited work.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fde1dadf-855e-4a20-812c-122b094b1697 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 26

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Observation 9dfa9af7-d6d7-47d1-9e3f-5227d320b560 · outbound

This paper cites Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:59:44.927584Z digest=sha256:21ad63de0e4c2245af826c374089f43db9dd40062573aee822220f999aa738df

Observation a4cd64f7-23be-4921-8194-0b4bb2f2d5d7 · outbound

This paper cites A New Benchmark and Reverse Validation Method for Passage-level Hallucination Detection.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models A New Benchmark and Reverse Validation Method for Passage-level Hallucination Detection

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:59:45.249502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-07T05:59:45.006815Z digest=sha256:702d1e80a5bd61ef79054bfee79ef716c895f06ccfaf772961324777869bb8dd

Observation 08d569c9-c2eb-4d08-b6ff-f8ce7a503eca · outbound

This paper cites KnowHalu: Hallucination Detection via Multi-Form Knowledge Based Factual Checking.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models KnowHalu: Hallucination Detection via Multi-Form Knowledge Based Factual Checking

Reference 29

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:59:45.064636Z digest=sha256:8afb0f05ff6153906c0e99f9e1464209cc8a7fa242812eda531c33953bcf7b57

Observation 575a9984-3e2b-4e9e-8587-5e55ee9de3d1 · outbound

This paper cites Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models

Reference 30

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source=arxiv_source observed=2026-08-07T05:59:45.106922Z digest=sha256:2c92536ff85424d1474de34189535a7fb01ceb4e28e78b7716343906bdb20a8d

Observation 8408cbb2-990f-4293-9580-a39ebf4322b3 · outbound

This paper cites LIMA: Less Is More for Alignment.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models LIMA: Less Is More for Alignment

Reference 31

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source=arxiv_source observed=2026-08-07T05:59:45.140074Z digest=sha256:0e0aafda4a56f3047eee92371b17c0bc351b48777b693f80312d80ae76906257

Observation 4ae2b51f-ad35-4259-ae3c-6f8a2175515f · outbound

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Beyond Facts: Evaluating Intent Hallucination in Large Language Models online" 'onlinestring :=

Reference 32

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source=arxiv_source observed=2026-08-07T05:59:45.145255Z digest=sha256:1d0de3cf90ce9b1780fd9349ffe6a8858b5da31bf4ef21118d28c421acca501f

Observation c3eeb918-408b-422b-8dae-8a61df6d960c · outbound

This paper cites write newline.

Beyond Facts: Evaluating Intent Hallucination in Large Language Models write newline

Reference 33

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source=arxiv_source observed=2026-08-07T05:59:45.148904Z digest=sha256:a790dd120ce9544009ea38f22646abaaf3ba1e72f1bdb2f3bb95dc77495e63ae

Pith citing papers

No inbound Pith citation observations are available.