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Paper Citation Record · LEDGER

On Improving Faithfulness of Podcasts from Documents

As of 21 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.21961.

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

pith.paper-citation-record.v1
2607.21961 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T06:16:50.386656Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

42 of 42 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 91b2d27d-794b-4146-87b1-0c96bf64eeaa · outbound

This paper cites an unresolved cited work.

On Improving Faithfulness of Podcasts from Documents Unresolved cited work

Reference 1

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Observation ba86d4ac-f080-43b0-b476-ababc65e90e4 · outbound

This paper cites an unresolved cited work.

On Improving Faithfulness of Podcasts from Documents Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-01T06:16:46.083787Z digest=sha256:b07b65c6193bf5a9413bbc17e005edbbac30ddc0ae5557ef87a0c449914e6d94

Observation 602aae32-65e7-4f7d-90c0-a02f81874c2b · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

On Improving Faithfulness of Podcasts from Documents The Fourteenth International Conference on Learning Representations , year=

Reference 3

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Observation 55fdb3b8-085c-4122-8830-7101b23f0f7f · outbound

This paper cites arXiv preprint arXiv:2601.14903 , year=.

On Improving Faithfulness of Podcasts from Documents arXiv preprint arXiv:2601.14903 , year=

Reference 4

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Observation 1c3e07c5-9150-4cd0-ba78-0af40a43d82f · outbound

This paper cites Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

On Improving Faithfulness of Podcasts from Documents Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 5

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source=arxiv_source observed=2026-08-01T06:16:46.426583Z digest=sha256:e6920a96544370b7150ecda25da74493ef47414efd16bc8ec19eb3d8ba4111dd

Observation 21188c70-f3a6-443b-ba0f-f0b5ba9913e0 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

On Improving Faithfulness of Podcasts from Documents BERTScore: Evaluating Text Generation with BERT

Reference 6

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Observation 672ceb14-bce7-4c34-9e1a-62e1693f6306 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=.

On Improving Faithfulness of Podcasts from Documents Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=

Reference 7

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no resolver link, observed 2026-08-01T06:16:46.532659Z

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source=arxiv_source observed=2026-08-01T06:16:46.532659Z digest=sha256:60d358f70423b9e852de33c7037ccc1c1b0747e727929df6afb2ef4f67c94be4

Observation 6d14fe95-0e9f-47ea-a6ce-2f035539a1ca · outbound

This paper cites Proceedings of the 2023 conference on empirical methods in natural language processing , pages=.

On Improving Faithfulness of Podcasts from Documents Proceedings of the 2023 conference on empirical methods in natural language processing , pages=

Reference 8

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source=arxiv_source observed=2026-08-01T06:16:46.652774Z digest=sha256:be19b3f7ed4e506cfe092297eeb70facdcce60ec85a0ce6fd13ce8f3983c03f2

Observation c18bbb8c-53cf-4bea-9c84-34c5d5edb851 · outbound

This paper cites N exus S um: Hierarchical LLM Agents for Long-Form Narrative Summarization.

On Improving Faithfulness of Podcasts from Documents N exus S um: Hierarchical LLM Agents for Long-Form Narrative Summarization

Reference 9

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source=arxiv_source observed=2026-08-01T06:16:46.748088Z digest=sha256:f338e4cffe18f338da6e2ee621e475095e5528a00882ed5b9ce0f8b0742859d0

Observation 7b567bce-7bd3-4a48-a3f0-4f2f291598c9 · outbound

This paper cites Transactions of the Association for Computational Linguistics , volume=.

On Improving Faithfulness of Podcasts from Documents Transactions of the Association for Computational Linguistics , volume=

Reference 10

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Observation 8b762ec4-8f57-4ddd-a34d-aeceb3506812 · outbound

This paper cites Knowledge and Information Systems , volume=.

On Improving Faithfulness of Podcasts from Documents Knowledge and Information Systems , volume=

Reference 11

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source=arxiv_source observed=2026-08-01T06:16:46.942439Z digest=sha256:ff21bcc4f7c51ad1e42cf3cdb8fe37986bd91a3ef3a7d9e257640f2fc1fcc42e

Observation ec7c721e-b3a6-41fc-94c1-8eb18d827e7e · outbound

This paper cites BELLE : A Bi-Level Multi-Agent Reasoning Framework for Multi-Hop Question Answering.

On Improving Faithfulness of Podcasts from Documents BELLE : A Bi-Level Multi-Agent Reasoning Framework for Multi-Hop Question Answering

Reference 12

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source=arxiv_source observed=2026-08-01T06:16:47.050104Z digest=sha256:c9ce9c93fb32736c1a83ab4a9d3d1c9e18d90364dc37f83560e819d9e5a56de7

Observation 34d74846-44db-44ec-9118-70bd2a9f6973 · outbound

This paper cites Beyond Prompting: An Efficient Embedding Framework for Open-Domain Question Answering.

On Improving Faithfulness of Podcasts from Documents Beyond Prompting: An Efficient Embedding Framework for Open-Domain Question Answering

Reference 13

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-01T06:16:47.157598Z digest=sha256:17aad9b1fac17847eb46f599d2a507445a7a51967fcc2de61cb0253ac8e6f534

Observation dddc0afc-24dc-4a2f-b363-28f03c77168c · outbound

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

On Improving Faithfulness of Podcasts from Documents FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"

Reference 14

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source=arxiv_source observed=2026-08-01T06:16:47.255239Z digest=sha256:9abfd27796a1cb3222151191307b672aff20cc27d4ad2be76bf7f4929ae63ab4

Observation d247ddde-4d74-4867-b342-1a6f47a54b8b · outbound

This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=.

On Improving Faithfulness of Podcasts from Documents Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 15

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Observation 2d87af71-861a-4697-8d33-70751402f0ab · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2023 , pages=.

On Improving Faithfulness of Podcasts from Documents Findings of the Association for Computational Linguistics: ACL 2023 , pages=

Reference 16

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Observation de7bb1ed-517d-45bb-bdaa-b0ff8a736d82 · outbound

This paper cites P od A gent: A Comprehensive Framework for Podcast Generation.

On Improving Faithfulness of Podcasts from Documents P od A gent: A Comprehensive Framework for Podcast Generation

Reference 17

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-01T06:16:47.582226Z digest=sha256:c23826a5ad45120be368a386b1fecceeb21fe2db696617ae4515326fe30d7d96

Observation bd275063-2a3e-49c6-befd-d376c7777a91 · outbound

This paper cites MoonCast: High-Quality Zero-Shot Podcast Generation.

On Improving Faithfulness of Podcasts from Documents MoonCast: High-Quality Zero-Shot Podcast Generation

Reference 18

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Observation f305a586-e168-408c-81b9-9572c2c199b1 · outbound

This paper cites CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models.

On Improving Faithfulness of Podcasts from Documents CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models

Reference 19

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Observation 9b424fa2-51f7-4e27-b623-80d7b4eb73d1 · outbound

This paper cites GPT-4 Technical Report.

On Improving Faithfulness of Podcasts from Documents GPT-4 Technical Report

Reference 20

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Observation 18d17965-422e-4275-b06a-8912318cdf1a · outbound

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On Improving Faithfulness of Podcasts from Documents 5 Technical Report , author=

Reference 21

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Observation d92d8f99-e0c4-40a7-9385-91a2ef152776 · outbound

This paper cites The Llama 3 Herd of Models.

On Improving Faithfulness of Podcasts from Documents The Llama 3 Herd of Models

Reference 22

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Observation d40cf721-73a1-4e92-a91b-2daefd201307 · outbound

This paper cites Mapping the Podcast Ecosystem with the Structured Podcast Research Corpus.

On Improving Faithfulness of Podcasts from Documents Mapping the Podcast Ecosystem with the Structured Podcast Research Corpus

Reference 23

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Observation dcc53cac-f234-4b87-a5be-bc5612885305 · outbound

This paper cites Groundedness in Retrieval-augmented Long-form Generation: An Empirical Study.

On Improving Faithfulness of Podcasts from Documents Groundedness in Retrieval-augmented Long-form Generation: An Empirical Study

Reference 24

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Observation 9f18dead-5f38-415b-aa03-e63078cebf4f · outbound

This paper cites ACM computing surveys , volume=.

On Improving Faithfulness of Podcasts from Documents ACM computing surveys , volume=

Reference 25

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Observation 00063696-3bec-407a-b6c7-9cfa18d7bcff · outbound

This paper cites Findings of the Association for Computational Linguistics: EACL 2024 , pages=.

On Improving Faithfulness of Podcasts from Documents Findings of the Association for Computational Linguistics: EACL 2024 , pages=

Reference 26

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Observation 389480f0-2a14-4a3d-acd1-73b38222635a · outbound

This paper cites Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , pages=.

On Improving Faithfulness of Podcasts from Documents Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 27

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Observation 66d42f5f-373e-4b61-a905-82831e486a61 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2023 , pages=.

On Improving Faithfulness of Podcasts from Documents Findings of the Association for Computational Linguistics: ACL 2023 , pages=

Reference 28

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Observation 1bd9e8f9-2740-4d83-a042-db5508d699dc · outbound

This paper cites Trusting Your Evidence: Hallucinate Less with Context-aware Decoding.

On Improving Faithfulness of Podcasts from Documents Trusting Your Evidence: Hallucinate Less with Context-aware Decoding

Reference 29

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Observation 37cc3830-372c-4184-8ab8-b4aed08c1dda · outbound

This paper cites Dynamic Attention-Guided Context Decoding for Mitigating Context Faithfulness Hallucinations in Large Language Models.

On Improving Faithfulness of Podcasts from Documents Dynamic Attention-Guided Context Decoding for Mitigating Context Faithfulness Hallucinations in Large Language Models

Reference 30

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation cfa885c8-3619-4942-9adf-6dd9a9cd82ee · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2021 , pages=.

On Improving Faithfulness of Podcasts from Documents Findings of the Association for Computational Linguistics: EMNLP 2021 , pages=

Reference 31

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Observation ab8cd358-15ac-4786-b755-87b4167a0d20 · outbound

This paper cites an unresolved cited work.

On Improving Faithfulness of Podcasts from Documents Unresolved cited work

Reference 32

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Observation bdff0c6e-68ab-4ab5-adaa-bb3d34b99132 · outbound

This paper cites Transactions of the Association for Computational Linguistics , volume=.

On Improving Faithfulness of Podcasts from Documents Transactions of the Association for Computational Linguistics , volume=

Reference 33

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Observation 5fb8c618-d6bc-4ab5-aae6-aaedb80e86b5 · outbound

This paper cites Advances in neural information processing systems , volume=.

On Improving Faithfulness of Podcasts from Documents Advances in neural information processing systems , volume=

Reference 34

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Observation 919eb7a6-139f-40b3-943d-4bc506f86cb4 · outbound

This paper cites Transactions of the Association for Computational Linguistics , volume=.

On Improving Faithfulness of Podcasts from Documents Transactions of the Association for Computational Linguistics , volume=

Reference 35

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Observation 583e81b5-63de-409e-87bc-f4e7ed3c4575 · outbound

This paper cites Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference.

On Improving Faithfulness of Podcasts from Documents Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Reference 36

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source=arxiv_source observed=2026-08-01T06:16:49.812857Z digest=sha256:68708462b372fc632119ad3964f0f525585f0b8543338460adfab2ede223fdda

Observation 6058a2a7-e41b-4c05-8df1-0cb195e9b6cb · outbound

This paper cites , author=.

On Improving Faithfulness of Podcasts from Documents , author=

Reference 37

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Observation 8b6e88a8-033f-4cce-921f-21ff3aa367b6 · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

On Improving Faithfulness of Podcasts from Documents Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:16:49.967684Z digest=sha256:e43e6d1676893e2174e57b422616c4d4893744d810d65655c2e64cedfb28c868

Observation f9584782-4d6b-4a6e-bc93-0e7c80b81499 · outbound

This paper cites Steering Language Models With Activation Engineering.

On Improving Faithfulness of Podcasts from Documents Steering Language Models With Activation Engineering

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-01T06:16:50.061829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:16:50.061829Z digest=sha256:6753b9f085133696462b5632a1544708b23228c2ed5703beb8bd6d540ebf7268

Observation 09bf5471-d9d7-44fa-aec1-d13352510aa5 · outbound

This paper cites Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Models.

On Improving Faithfulness of Podcasts from Documents Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-01T06:16:50.182263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:16:50.182263Z digest=sha256:60798e5699d0f2128cb64ca4a86a5e982d643abad0ee9d2fbbae87b9dc2a1986

Observation c2269f24-c764-441d-a1c1-51932d341fd0 · outbound

This paper cites SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models.

On Improving Faithfulness of Podcasts from Documents SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-01T06:16:50.260564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:16:50.260564Z digest=sha256:884538176338d882e875965b45084ced9ea63efea8e541276936836faa56d247

Observation 1023d59b-9cbc-4a6f-bc8f-2a27341c36e1 · outbound

This paper cites SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence.

On Improving Faithfulness of Podcasts from Documents SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-01T06:16:50.386656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:16:50.386656Z digest=sha256:246459c17b29664c8077b5829f8349ed3d975d8acd34be3fa17b092d6eb9391b

Pith citing papers

No inbound Pith citation observations are available.