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Paper Citation Record · LEDGER

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language

As of 9 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2607.15607.

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

pith.paper-citation-record.v1
2607.15607 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:51:14.735700Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

11 of 11 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a928cbed-a86e-4d9c-af22-4efa6fae7f79 · outbound

This paper cites Fact-checking the output of large language models via token-level uncertainty quantifica- tion.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language Fact-checking the output of large language models via token-level uncertainty quantifica- tion

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.719853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.719853Z digest=sha256:14b5211389b9de99a285165b6965316a1e5824c5ba4383ba8fa05d654941a5b6

Observation 7858fbef-842e-43aa-aafe-232a6b9e67d9 · outbound

This paper cites Probabilistic distances-based hal- lucination detection in llms with rag.arXiv preprint arXiv:2506.09886,.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language Probabilistic distances-based hal- lucination detection in llms with rag.arXiv preprint arXiv:2506.09886,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.728084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.728084Z digest=sha256:b15c4588310f9a7df0619f861da2e8861ce5c225573ce14e3ec0c9fc79983acd

Observation 284cab8c-bda8-4fff-88b6-d2ffffad8c1f · outbound

This paper cites Multilingual E5 Text Embeddings: A Technical Report.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language Multilingual E5 Text Embeddings: A Technical Report

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.735700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.735700Z digest=sha256:4c0164f9eb64c44472186dd57f13987a8932a611cb23fd7a3d7162282ec350c9

Observation 1de83f68-e33e-48ad-9e39-e39798799bbf · outbound

This paper cites Lookback lens: De- tecting and mitigating contextual hallucinations in large language models using only attention maps.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language Lookback lens: De- tecting and mitigating contextual hallucinations in large language models using only attention maps

Reference 1964

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.711391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.711391Z digest=sha256:93ec2a1dd26b4f61581bb46fb6589a24a17e10541fd1ab6de6e4d722d3a9e746

Observation 65ef0de8-5d3f-4f03-9329-70638fc8e251 · outbound

This paper cites How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection

Reference 2012

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.722373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.722373Z digest=sha256:3d493aa572fa03f68db51af279a21ab7844bbf7103dd11569196c4b9d254225d

Observation d8570bf7-8fa7-4897-976d-e58bb97b232e · outbound

This paper cites A Wild Bootstrap for Degenerate Kernel Tests.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language A Wild Bootstrap for Degenerate Kernel Tests

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.713897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.713897Z digest=sha256:e73ce1b3c66fa9fac9d19a60786f42392f1b551331aa5189baa621510f85cbc6

Observation 6f733c9b-702d-47d5-8d97-cd0fafd3ea62 · outbound

This paper cites Hallucination Detection: A Probabilistic Framework Using Embeddings Distance Analysis.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language Hallucination Detection: A Probabilistic Framework Using Embeddings Distance Analysis

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.730723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.730723Z digest=sha256:464366b05d55540ba560bfc7b8d7fdd6549524e1e1287b1761d7d612df2356f7

Observation ede3c298-fa34-48d9-afd2-f7ad1bbbf8a3 · outbound

This paper cites DeepSeek-V3 Technical Report.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language DeepSeek-V3 Technical Report

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.725240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.725240Z digest=sha256:0dbd0ebe6665d902febbd76e7cb4ae199fc2ad67c645c0e2c9347276712dc294

Observation 959bc4f7-5038-4b2c-87b5-c60b0691f6cd · outbound

This paper cites org/papers/v24/21-1289.html.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language org/papers/v24/21-1289.html

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.733302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.733302Z digest=sha256:9fc3c4e31a52a729b061066f42290840b580ee7191b031fb15819804a4d8679c

Observation 5dd36564-c762-4b04-9b58-7d221b3f4581 · outbound

This paper cites URL https://aclanthology.org/2024.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language URL https://aclanthology.org/2024

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.716896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.716896Z digest=sha256:2c9a6283e54d83daf764c5fd603a4c449feffcac3cc5f6cc1814008306310429

Observation 0def62e9-d747-4470-aa5d-7993a86e5bbe · outbound

This paper cites Hallucination Detection in LLMs with Topological Divergence on Attention Graphs.

ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language Hallucination Detection in LLMs with Topological Divergence on Attention Graphs

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-01T22:51:14.709034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:51:14.709034Z digest=sha256:5d656643cab44255301395664ed5cff1fd8bcd237a5e16bc14555f8766377988

Pith citing papers

No inbound Pith citation observations are available.