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Paper Citation Record · LEDGER

Controllable Text Generation for Large Language Models: A Survey

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2408.12599.

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

pith.paper-citation-record.v1
2408.12599 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 30 of 30 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 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:14:34.050480Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T12:09:48.829945Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dc250669-7669-49bd-8277-958dea84a5d3 · inbound

Vulnerability Mitigation for Safety-Aligned Language Models via Debiasing cites this paper.

Vulnerability Mitigation for Safety-Aligned Language Models via Debiasing Controllable Text Generation for Large Language Models: A Survey

Reference 26

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no resolver link, observed 2026-08-09T13:14:34.050480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T13:14:34.050480Z digest=sha256:b00cd5f5072a443e2a9d1a36d1b21fd7a199c6a8b080bf5e805a9d5f3807f343

Observation 4d97b2c8-357a-470f-8ada-2521b0871e72 · inbound

LIFEBench: Evaluating Length Instruction Following in Large Language Models cites this paper.

LIFEBench: Evaluating Length Instruction Following in Large Language Models Controllable Text Generation for Large Language Models: A Survey

Reference 62

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no resolver link, observed 2026-08-07T15:08:05.544649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:08:05.544649Z digest=sha256:59787ab3f43c9d03c78050121a0b64ce3d2cef28861e47ef05df9e426ee7be99

Observation 3ffc685f-ab4a-4baa-923c-52ef5ab7142b · inbound

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use cites this paper.

SweEval: Do LLMs Really Swear? A Safety Benchmark for Testing Limits for Enterprise Use Controllable Text Generation for Large Language Models: A Survey

Reference 24

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no resolver link, observed 2026-08-07T14:52:28.795914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:52:28.795914Z digest=sha256:8cf33ac74f4e9a6d3350aa0b52137bdb5900bb65ad66edb43bc58c19ad275a8c

Observation 6236afc4-aacb-4427-8c06-40057cd64048 · inbound

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs cites this paper.

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs Controllable Text Generation for Large Language Models: A Survey

Reference 33

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no resolver link, observed 2026-08-07T11:16:27.449644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:16:27.449644Z digest=sha256:ade4ff1e3b080a49709b44d1a95e524556ca2946cd8bf32a997fc9ca1c406607

Observation e8470a43-cf81-4a27-83ba-afc1589758a7 · inbound

Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation cites this paper.

Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation Controllable Text Generation for Large Language Models: A Survey

Reference 17

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unresolved
no resolver link, observed 2026-08-07T05:33:27.046164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:33:27.046164Z digest=sha256:eded08e52c7bbdfa614992665473056652e2988b648e9b3b1eea2a4157ad5cd9

Observation a115faf5-412f-4f6f-8eef-0217a7255e57 · inbound

MedReadCtrl: Personalizing medical text generation with readability-controlled instruction learning cites this paper.

MedReadCtrl: Personalizing medical text generation with readability-controlled instruction learning Controllable Text Generation for Large Language Models: A Survey

Reference 20

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unresolved
no resolver link, observed 2026-08-06T18:48:18.665928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:48:18.665928Z digest=sha256:bb87311a673ed0a18f9f379fcf0f397f87a3d00760f0494225699633253118bd

Observation 9c515621-e5ac-4977-a87f-92c132898a7b · inbound

A Mixture of Linear Corrections Generates Secure Code cites this paper.

A Mixture of Linear Corrections Generates Secure Code Controllable Text Generation for Large Language Models: A Survey

Reference 2

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unresolved
no resolver link, observed 2026-08-06T17:59:00.483831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:59:00.483831Z digest=sha256:3d5256314f5b930a64a04b6d9f25645910c8b0d68818097e144fa13c4d21f113

Observation 8b9499a2-6c12-46e6-8445-d54ddf696e76 · inbound

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction cites this paper.

A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction Controllable Text Generation for Large Language Models: A Survey

Reference 129

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no resolver link, observed 2026-08-06T13:54:39.934375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:54:39.934375Z digest=sha256:c6800641b87d43ae49ea6ea5189021c819f1415418802ca503cf4b9f96d70569

Observation a2d57a0c-f948-49ea-9b5a-ad14f76dadc6 · inbound

How Instruction-Tuning Imparts Length Control: A Cross-Lingual Mechanistic Analysis cites this paper.

How Instruction-Tuning Imparts Length Control: A Cross-Lingual Mechanistic Analysis Controllable Text Generation for Large Language Models: A Survey

Reference 7

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no resolver link, observed 2026-08-05T11:59:11.392923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:59:11.392923Z digest=sha256:a5de15d499c62601adbb226dce73471cfcf91b270f41f72e14cdbd7f73b70227

Observation c63c94e6-e38a-4352-87d2-16df7eec2bdf · inbound

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data Controllable Text Generation for Large Language Models: A Survey

Reference 125

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no resolver link, observed 2026-08-03T08:15:23.162196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T08:15:23.162196Z digest=sha256:5e0cc6670e0ec8ba78bfdef955eb0324d65d4da8f81dee709debe68075235851

Observation 6e9d3d31-4491-4679-90c7-ae031dec65c4 · inbound

Escaping the BLEU Trap: A Signal-Grounded Framework with Decoupled Semantic Guidance for EEG-to-Text Decoding cites this paper.

Escaping the BLEU Trap: A Signal-Grounded Framework with Decoupled Semantic Guidance for EEG-to-Text Decoding Controllable Text Generation for Large Language Models: A Survey

Reference 25

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no resolver link, observed 2026-08-03T03:27:34.509955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:27:34.509955Z digest=sha256:7b1153843ba34737a2967723d570342da7b6f2b55482b48a8e3f79d28cf88eca

Observation 2649b420-9e03-4515-af95-2ff4543743e8 · inbound

BiST: A Gold Standard Bangla-English Bilingual Corpus for Sentence Structure and Tense Classification with Inter-Annotator Agreement cites this paper.

BiST: A Gold Standard Bangla-English Bilingual Corpus for Sentence Structure and Tense Classification with Inter-Annotator Agreement Controllable Text Generation for Large Language Models: A Survey

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T23:00:50.628578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T19:23:19.091444Z digest=sha256:b1a6090cdc66deec97b3da6535b0c3981e24f87eeeb79c93c75efcc6cebe7413

Observation 3b836b1d-23ef-4a7c-818d-6b7c795d722b · inbound

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face cites this paper.

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face Controllable Text Generation for Large Language Models: A Survey

Reference 52

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verified exact
arxiv_id, observed 2026-05-10T23:20:54.663032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T19:11:27.071800Z digest=sha256:a950e08caa7624927cc4fdad773d8f2b7975dba65c2e4c8a991035fadb839fcc

Observation fd290df2-57f1-4d7a-a761-261ab9dc2ca1 · inbound

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face cites this paper.

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face Controllable Text Generation for Large Language Models: A Survey

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-02T16:43:11.612005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:43:11.612005Z digest=sha256:797bba1fe9ef45288d5b4aa3fbaf441d75b96476a8d634c86dc79046669b7266

Observation 26c51824-c9a6-49ae-8a46-4f26f64e7f41 · inbound

Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling cites this paper.

Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling Controllable Text Generation for Large Language Models: A Survey

Reference 53

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metadata mismatch
arxiv_id, observed 2026-05-10T11:30:19.684706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T04:51:12.358148Z digest=sha256:54fc06445c4609bee9a0d06fc74ab393ee6710ee5037e2ef0c71aeea8ec0db07

Observation 6b36cda2-4388-4465-a8cb-7c97f455bd0d · inbound

From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents cites this paper.

From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents Controllable Text Generation for Large Language Models: A Survey

Reference 6

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metadata mismatch
arxiv_id, observed 2026-05-11T13:16:03.451434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T02:10:13.205879Z digest=sha256:378cc7f047801e7056eeaa8bb3a1dfe148647ee6bb117c22e434016099072069

Observation 6aa8a28f-b107-429e-a848-57494ac5774e · inbound

Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving cites this paper.

Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving Controllable Text Generation for Large Language Models: A Survey

Reference 94

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metadata mismatch
arxiv_id, observed 2026-05-11T13:46:04.272956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T00:37:55.147350Z digest=sha256:362eed5b42c551c08b2ffd35a6908302475064b43fa044e9ddc251a87ea7c733

Observation 7d0dd82e-e7a8-41df-a77e-92252569f6b5 · inbound

OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving cites this paper.

OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving Controllable Text Generation for Large Language Models: A Survey

Reference 110

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metadata mismatch
arxiv_id, observed 2026-05-11T14:21:03.963008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-09T22:04:19.654714Z digest=sha256:31f2a4ac35ab9b40b353dc57de095e29a36fc77d5ae883e4095932c1a2b32ea3

Observation 72d60ea4-8bfd-46a6-8a75-d774ca413d0a · inbound

Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment cites this paper.

Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment Controllable Text Generation for Large Language Models: A Survey

Reference 9

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verified exact
arxiv_id, observed 2026-05-11T21:46:24.496056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T04:29:54.013922Z digest=sha256:c72f52d5f83caa713f74436be4341b1c838f93cc89ca9c870153ed6ec97c25a3

Observation 9f53f309-14c8-426f-a25f-ab34850868fe · inbound

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs cites this paper.

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs Controllable Text Generation for Large Language Models: A Survey

Reference 6

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verified exact
arxiv_id, observed 2026-05-11T03:40:53.489058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T03:40:04.692279Z digest=sha256:07a9d5468dcfc74972f46f38ca0755689afd951e93532c80a58fe3ffb6e0c2d9

Observation 216f3c25-bb80-4c75-bbb8-d924ee8000b1 · inbound

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs cites this paper.

Benchmarking EngGPT2-16B-A3B against Comparable Italian and International Open-source LLMs Controllable Text Generation for Large Language Models: A Survey

Reference 6

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verified exact
arxiv_id, observed 2026-05-21T08:19:52.982997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T08:14:55.858466Z digest=sha256:f4e96a268f445cdf3328ac7dc7a66c25d0db182d20ac8b971c54455f45c26dd9

Observation 2be33b9e-08ca-4888-9779-01140ef8321a · inbound

Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study cites this paper.

Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study Controllable Text Generation for Large Language Models: A Survey

Reference 23

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metadata mismatch
arxiv_id, observed 2026-05-15T05:15:03.160302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T05:11:47.070579Z digest=sha256:850eb4f832950053f558fe2236e3bea554caed70011d1a07d61e419720880ec8

Observation 21a7719c-ca4e-445f-b560-4491a144ad2c · inbound

Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study cites this paper.

Measuring and Mitigating Toxicity in Large Language Models: A Comprehensive Replication Study Controllable Text Generation for Large Language Models: A Survey

Reference 23

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metadata mismatch
arxiv_id, observed 2026-05-19T13:42:19.217187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T13:41:37.102367Z digest=sha256:0afaefd19ff080a8c1ca6a3de347e5d6936f087dccb404fffd73eeef25e2ac0f

Observation 3f1e2882-d11c-40b2-86ab-62d39294281b · inbound

Position: AI Safety Requires Effective Controllability cites this paper.

Position: AI Safety Requires Effective Controllability Controllable Text Generation for Large Language Models: A Survey

Reference 31

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verified exact
arxiv_id, observed 2026-06-29T17:33:45.472841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T17:25:56.324612Z digest=sha256:52a0828e479094b2f909c504effc789f07713fa60d1df69363778634afe7b104

Observation b0b5e49d-8312-4400-9ab5-f6a2cf4d074a · inbound

Answer Engineering: Local Trajectory Editing for Protocol-Constrained Decision Making in Large Language Models cites this paper.

Answer Engineering: Local Trajectory Editing for Protocol-Constrained Decision Making in Large Language Models Controllable Text Generation for Large Language Models: A Survey

Reference 22

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metadata mismatch
arxiv_id, observed 2026-07-04T06:49:37.536274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T14:13:13.678245Z digest=sha256:26bda23f3501256515676b08f72981159bbc0a6e284a70a19704c515b4a99d0a

Observation 8222aa88-a189-4e4f-a111-8122a4d3baf4 · inbound

Towards Fast Domain Adaptation and Fine-Grained User Simulation for Evaluating Conversational Recommender Systems cites this paper.

Towards Fast Domain Adaptation and Fine-Grained User Simulation for Evaluating Conversational Recommender Systems Controllable Text Generation for Large Language Models: A Survey

Reference 17

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arxiv_id, observed 2026-07-04T12:09:48.831371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T07:13:21.198407Z digest=sha256:2036c89a5a920965cc41d5bff1af9f111b2057ace4b880b4224fe3ab79d8b713

Observation a12d5b3c-7012-4091-91a0-e64e711a3a52 · inbound

Do Sparse Autoencoders Learn Meaningful Concept Hierarchies? cites this paper.

Do Sparse Autoencoders Learn Meaningful Concept Hierarchies? Controllable Text Generation for Large Language Models: A Survey

Reference 27

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verified exact
arxiv_id, observed 2026-07-04T10:29:45.402400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T08:46:48.220801Z digest=sha256:20f59ce5a8ee4b6dfd008dca4e41e7045404c90dbbeb7a15bec81b37abb95b49

Observation 0bf177bc-c5ed-4f39-bd0f-c37d476abe53 · inbound

Multi-Objective Exploration and Preference Optimization via Mutual Information cites this paper.

Multi-Objective Exploration and Preference Optimization via Mutual Information Controllable Text Generation for Large Language Models: A Survey

Reference 86

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metadata mismatch
arxiv_id, observed 2026-07-03T21:18:58.013616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-03T21:17:46.551850Z digest=sha256:9567081453f817ec29b95fe8da7ccde7e841f6da69bdce572d3149fcf7b8b4ce

Observation 9f7d682d-d0ff-467c-8d35-9f8a56dd3659 · inbound

Aligning Language Models with Selective Prediction cites this paper.

Aligning Language Models with Selective Prediction Controllable Text Generation for Large Language Models: A Survey

Reference 42

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no resolver link, observed 2026-07-12T01:51:25.883463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T01:51:25.883463Z digest=sha256:0258f912c8ad08378e0ff09e2e6539ea1192da35dc14f448de734d09858fc2d7

Observation cee07121-55b0-41e7-8ebb-21a07407df3f · inbound

IFHierBench: Hierarchical Instruction Following for Large Language Models cites this paper.

IFHierBench: Hierarchical Instruction Following for Large Language Models Controllable Text Generation for Large Language Models: A Survey

Reference 2025

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unresolved
no resolver link, observed 2026-07-31T23:14:22.844588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:14:22.844588Z digest=sha256:d747feeab7fd0fc87ec541fb0ff8ee16b6fa3cb080609e7d6284d385c9913508