Paper Citation Record · LEDGER

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)

As of 19 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.04223.

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

pith.paper-citation-record.v1
2607.04223 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T20:50:52.068889Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

22 of 22 outbound references displayed

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unresolved22
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da7a38df-1f08-44b6-a687-6f4ff2905b22 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive NLP tasks,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) Retrieval- augmented generation for knowledge-intensive NLP tasks,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06236f93-ef52-4afe-a2d9-45376ff2b1a6 · outbound

This paper cites Survey of halluci- nation in natural language generation,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) Survey of halluci- nation in natural language generation,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation d518fe9c-8a7b-41f9-ba29-10a48ef92cde · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation f67e9a36-9a39-46fb-9bfd-f59566c94407 · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) Detecting hallucinations in large language models using semantic entropy,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 3441851f-e2ba-49e6-a364-862901749dd9 · outbound

This paper cites INSIDE: LLMs’ internal states retain the power of hallucination detection,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) INSIDE: LLMs’ internal states retain the power of hallucination detection,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Unavailable: canonical work link unavailable.

Observation 1ab14bca-965d-4639-af85-6470a02e88b1 · outbound

This paper cites LLM-Check: Investigating detection of hallucinations in large language models,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) LLM-Check: Investigating detection of hallucinations in large language models,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 5548c19f-97eb-4282-9af5-2e6af6db3f82 · outbound

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

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) SelfCheck- GPT: Zero-resource black-box hallucination detection for generative large language models,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 4b7c4dfb-3da2-4479-8266-a3113f1021d0 · outbound

This paper cites FActScore: Fine-grained atomic evaluation of factual precision in long form text generation,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) FActScore: Fine-grained atomic evaluation of factual precision in long form text generation,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation c09a48eb-58b0-42a6-ac08-8767b863c748 · outbound

This paper cites ContextCite: Attributing model generation to context,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) ContextCite: Attributing model generation to context,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 95766cb1-b7a4-4cdf-a7e3-20a0dd102631 · outbound

This paper cites Lookback lens: Detecting and mitigating contextual hallucinations in large language models using only attention maps,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) Lookback lens: Detecting and mitigating contextual hallucinations in large language models using only attention maps,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation e744a48c-a74a-4303-ae16-d629c251c2af · outbound

This paper cites ReDeEP: Detecting hallucination in retrieval-augmented generation via mechanistic inter- pretability,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) ReDeEP: Detecting hallucination in retrieval-augmented generation via mechanistic inter- pretability,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 1e84af66-4520-4cc2-ae5d-7a4488b98034 · outbound

This paper cites LUMINA: Detecting hallucinations in RAG systems with context-knowledge signals,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) LUMINA: Detecting hallucinations in RAG systems with context-knowledge signals,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Unavailable: canonical work link unavailable.

Observation ec383540-15f7-4d2b-9eb6-00d4be92fb60 · outbound

This paper cites RAGTruth: A hallucination corpus for developing trustworthy retrieval- augmented language models,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) RAGTruth: A hallucination corpus for developing trustworthy retrieval- augmented language models,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 0cfa3811-73b5-407e-9d82-0d28fd2aaeb1 · outbound

This paper cites RAGAs: Automated evaluation of retrieval augmented generation,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) RAGAs: Automated evaluation of retrieval augmented generation,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 5e0df7e0-e6b2-407b-874c-21e0c595bb3f · outbound

This paper cites LettuceDetect: A Hallucination Detection Framework for RAG Applications.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) LettuceDetect: A Hallucination Detection Framework for RAG Applications

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation e146cd35-e64d-4732-88a8-ac95e0e7ff0a · outbound

This paper cites Fractal attractors in random nonlinear it- erated function systems: Existence, stability, and dimen- sional properties,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) Fractal attractors in random nonlinear it- erated function systems: Existence, stability, and dimen- sional properties,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 47e45e25-4170-455f-b7d0-7c77770a3aeb · outbound

This paper cites Light- GBM: A highly efficient gradient boosting decision tree,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) Light- GBM: A highly efficient gradient boosting decision tree,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e361f44-56da-457d-8594-a1d9e07c8505 · outbound

This paper cites TofuEval: Evaluating hallucinations of large language models on topic-focused dialogue summarization,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) TofuEval: Evaluating hallucinations of large language models on topic-focused dialogue summarization,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 5b7dc90e-13e5-4899-94aa-e226a6dc749b · outbound

This paper cites MeetingBank: A benchmark dataset for meeting summarization,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) MeetingBank: A benchmark dataset for meeting summarization,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation d581c92c-f77e-42f8-9bf4-92d55a11760f · outbound

This paper cites RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation cd4ffd5d-7f52-4a85-bf6e-a9207b65dc8b · outbound

This paper cites Qwen2.5 technical report,.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) Qwen2.5 technical report,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Observation 7f2a0416-7b7d-4f59-ad65-178dd98023b9 · outbound

This paper cites SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model.

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP) SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-11T20:50:52.068889Z

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Pith citing papers

No inbound Pith citation observations are available.