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Paper Citation Record · LEDGER

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction

As of 3 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.00008.

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

pith.paper-citation-record.v1
2607.00008 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-02T23:54:20.000531Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-02T06:30:47.504484+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 exact8
  • verified fuzzy12
  • unresolved2
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch10

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 36a077ea-1c08-4d23-ac86-aba470560ac2 · outbound

This paper cites 2024 , url=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction 2024 , url=

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.400056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:9b41ef5c56ea6469ff74b00e1f847fa14452e8857e94c1522ecb7b7f2104f73b

Observation 66383a67-1513-49e5-808c-e5f2c902c9b3 · outbound

This paper cites Proceedings of the 46th international ACM SIGIR conference on research and development in information retrieval , pages=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Proceedings of the 46th international ACM SIGIR conference on research and development in information retrieval , pages=

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.417012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:fca2df6cb0d1ef2cd30022e7b2ed052c48545dafd09e784f37de38c9016fdf30

Observation 16985cfd-001c-4e0f-a550-4e7e6e2e1458 · outbound

This paper cites Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T23:57:27.956247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:f5e8da687cabae473d070d7aa6a07272b234e7e642a5d825cf177adb73eb3374

Observation 531ac342-e7a4-47ab-928a-203ab4c7f310 · outbound

This paper cites Journal of Cleaner Production , volume =.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Journal of Cleaner Production , volume =

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:57:27.788863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:5ac0dd0f7897c7f1cf9b81caa8ce561a66cf50fcd71abe2c3b7f2e45db9a286f

Observation 081aeb5b-0115-4d81-871e-0ebd6ea695ba · outbound

This paper cites Information Integration and Web Intelligence: 26th International Conference, IiWAS 2024, Bratislava, Slovak Republic, December 2–4, 2024, Proceedings, Part I , pages =.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Information Integration and Web Intelligence: 26th International Conference, IiWAS 2024, Bratislava, Slovak Republic, December 2–4, 2024, Proceedings, Part I , pages =

Reference 5

Resolution
verified exact
doi, observed 2026-07-02T23:57:27.767931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:f099db64732640f22e74ce244c92f725bf2219a3aabf7a4ec696ed35fe1723e2

Observation 0ad5cf36-7017-43e9-8860-207333b2e1e7 · outbound

This paper cites doi: 10.1038/s41467-024-45563-x.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction doi: 10.1038/s41467-024-45563-x

Reference 6

Resolution
metadata mismatch
doi, observed 2026-07-02T23:57:27.770200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:987043959f67c8ca28dfd859ead1069ac7821d003a9ae7b81d8195376fe132ff

Observation e3748653-ffd0-434b-8707-7d34ecef2e04 · outbound

This paper cites Learning to Extract Structured Entities Using Language Models.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Learning to Extract Structured Entities Using Language Models

Reference 7

Resolution
verified exact
doi, observed 2026-07-02T23:57:27.793455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:d720425ae840c0c5853819188a8f68af457e3a5e6d428806a980e76dbd829b20

Observation a77489aa-b767-44b3-a4f8-29f3b4a7bb07 · outbound

This paper cites doi: 10.18653/v1/2022.emnlp-main.130.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction doi: 10.18653/v1/2022.emnlp-main.130

Reference 8

Resolution
metadata mismatch
doi, observed 2026-07-02T23:57:27.780659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:81241d0074137abeab6d270e290ae8ddc4299c6b1b8e4bee1c47435b91960b8f

Observation 0c113759-5881-4f3d-9a93-394483587869 · outbound

This paper cites A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.410482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:9570c7da97a1d8aac097567562e1963595eecea77595a87fb25729b7245046e5

Observation 5a490c8e-9c00-486c-8bb5-dd81790e0ae2 · outbound

This paper cites 2023 , editor =.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction 2023 , editor =

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.406935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:94c465b2ff729d6bab2d0d767909e526d5b8f7639f418cbf2e0885659230bd55

Observation 6d194ca7-85ba-4c09-a625-c72dd0e51f00 · outbound

This paper cites Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product

Reference 11

Resolution
verified exact
doi, observed 2026-07-02T23:57:27.775750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:83257025238dca175c5748d688e60495d5119dcfb1174a435c003ad3ad9b2b3a

Observation eb3daf04-b65f-4cac-8a8d-2bde0d7ee427 · outbound

This paper cites 2025 , eprint=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction 2025 , eprint=

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.413718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:f37280a01d1cfc740d5f3c26101d9921ddedeaaa3c68ffbf83c597d76b907788

Observation b3bfffb3-ed14-4097-8b93-b3a926e8ccc4 · outbound

This paper cites TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning

Reference 13

Resolution
verified exact
doi, observed 2026-07-02T23:57:27.772972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:69306f75d759c535594bc2a99f549482ea2c7d73c9d1462f780c5975457d0e29

Observation 74f9099d-6783-418c-b3aa-1c1d8dbffb6f · outbound

This paper cites doi: 10.18653/v1/2023.acl-long.551.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction doi: 10.18653/v1/2023.acl-long.551

Reference 14

Resolution
metadata mismatch
doi, observed 2026-07-02T23:57:27.778339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:0fa0fececd428e145dc9503de64aa9da63bde1169953a495e821568f11e3ef73

Observation 642916e7-8cb5-4bce-a051-ca5f60ed6cd9 · outbound

This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang

Reference 15

Resolution
verified exact
doi, observed 2026-07-02T23:57:27.791104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:fc58c3ab37859a827620427b5d8c1aeacec92efbe49574c9cb542510e2dbad99

Observation 183faf77-9695-40c8-8828-4805c743ba9e · outbound

This paper cites InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T23:57:27.961582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:53f7c57a1987aac17ba83bd663d29010c60d825381ad7a56830fa8bd6f8dab1c

Observation 959a3249-6b42-4164-b9a5-73f6cb409c30 · outbound

This paper cites ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T23:57:27.947908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:1316843390daf2fa6baa74852e80f06d8969b7643d48eef0a4c50a2b93a1eeec

Observation 746ce989-edc6-459f-b64c-8e05f1b0553d · outbound

This paper cites ExtractGPT: Exploring the Potential of Large Language Models for Product Attribute Value Extraction.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction ExtractGPT: Exploring the Potential of Large Language Models for Product Attribute Value Extraction

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:57:27.958863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:e0f65c3fcc7a9e528e44cf380a1b52fc5e9d1548d92a63e2295a5059191fb129

Observation 7e422936-dcc0-406d-838f-67ade4d0141e · outbound

This paper cites Advances in Neural Information Processing Systems , editor =.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Advances in Neural Information Processing Systems , editor =

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.403616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:3982329ed8a38b493e0528fcaf87ba0169046d8ccf2bd0315f69625acd7e94c1

Observation c8ea61e2-9853-4387-831a-153330075c28 · outbound

This paper cites 2024 , eprint=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction 2024 , eprint=

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.432968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:ac73300addc509ae1f0782293f25f4e0d9332cf27f2db7972eb5c8c0de57cdb1

Observation aad320b5-96c3-461f-b86e-91841a3be374 · outbound

This paper cites Warren, Lu Cheng, Haidar M.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Warren, Lu Cheng, Haidar M

Reference 21

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T23:57:27.784095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:fbc69688ec292c803ff5fe7f19456826254debeee20f0e9f5e22c7a561f90988

Observation fac617a7-4207-4ea4-8249-5488fb07a8a7 · outbound

This paper cites Graph Retrieval-Augmented Generation: A Survey.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Graph Retrieval-Augmented Generation: A Survey

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T23:57:27.953422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:864c6f976841e46c871e02624a0740e3ab1038c5d6c5630a001c3b473ca7ffc4

Observation c11c5011-289f-4e5e-bdec-6b8f15ec75bd · outbound

This paper cites Knowledge Graph-based Retrieval-Augmented Generation for Schema Matching.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Knowledge Graph-based Retrieval-Augmented Generation for Schema Matching

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T23:57:27.950758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:c8ac851fe7c13595b795c6d29a3c02d4c61f1ee7e882a6de786767a11da78071

Observation 0ebee82b-14a4-4e2c-8dad-4735eb279538 · outbound

This paper cites An Enhanced Prompt-Based LLM Reasoning Scheme via Knowledge Graph-Integrated Collaboration.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction An Enhanced Prompt-Based LLM Reasoning Scheme via Knowledge Graph-Integrated Collaboration

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.440333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:987f2eddbeda21fbd6cb2ae936fdc05d59cfb863bbd42d1dfe95348309e9880b

Observation 765829e1-d5b0-4960-8422-3c71546108f1 · outbound

This paper cites Information Processing.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Information Processing

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T23:57:27.758929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:44bc6fe06fb115e6c9b0d67e12b88ccd29970fdddf4035c4fc582ddc78fa7277

Observation 47ee1e12-d07e-4146-8594-d2823934863a · outbound

This paper cites Large Language Models Encode Clinical Knowledge.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Large Language Models Encode Clinical Knowledge

Reference 26

Resolution
verified exact
doi, observed 2026-07-02T23:57:27.795871Z

Source-reported events for the cited work

correction dated 2023-07-27. Source: crossref record 10.1038/s41586-023-06455-0->10.1038/s41586-023-06291-2:correction, observed 2026-07-11T03:08:19.417011+00:00. This notice travels one citation hop only.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:4f4fd4f3bed096e39c05f7dd680a62c5df24c5af60a52eb2b80e8fc10ab88a74

Observation 2caa76fc-2795-4763-9744-12b4f4651b01 · outbound

This paper cites Breakthroughs in statistics: Methodology and distribution , pages=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Breakthroughs in statistics: Methodology and distribution , pages=

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.423579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:606264bcc2c28faf36c5f2daec53fcba2f52c86c505ff3c4af55a0dfdedb25bc

Observation f1c6243d-747c-4430-939d-b757f42b100a · outbound

This paper cites Biometrika , volume=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Biometrika , volume=

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.396587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:0734606298657b4256d905be34faf07ce8ae981ff0cef5d5e35c2629e5409dd5

Observation 29a0105f-d21d-49c8-ab19-738f05468a9e · outbound

This paper cites OpenAI , year=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction OpenAI , year=

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.420134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:aa1992e7aa42fb5cdc30ed8678b0ebbee6543ecd71a5ab90e9eafe185a11c473

Observation effd96f5-a4f5-4a30-afe3-f84558ae28f7 · outbound

This paper cites an unresolved cited work.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-07-05T17:31:22.427080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:4ec37c3150434108f7713c97043b2d7a18d86a1416d5aadbbb50bbf811f680a1

Observation 6d54d730-822e-4e12-a2fc-6f096089a1ee · outbound

This paper cites 2025 , howpublished =.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction 2025 , howpublished =

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-05T17:31:22.429910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:6804773897867a4e2d4b3e656c93e5dee04166ca45b15e9ffd79e7c1487b7300

Observation bfa312fa-475f-41fb-a768-ee45546c0f23 · outbound

This paper cites an unresolved cited work.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-07-05T17:31:22.443664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:f32e665fa539bc72a22c75001e34a2049e34f33bc22d59e4766c000b27ee3cbb

Observation a1b192df-ffc0-4fdc-ae1d-5294f86de764 · outbound

This paper cites OpenAI , year=.

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction OpenAI , year=

Reference 33

Resolution
parse uncertain
raw_fallback, observed 2026-07-05T17:31:22.436713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.

source=arxiv_source observed=2026-07-02T23:54:20.000531Z digest=sha256:615f7265db13f52b1c840c47f2fcbcc178533d3a0470bc51c992de02d892660b

Pith citing papers

No inbound Pith citation observations are available.