Paper Citation Record · LEDGER

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models

As of 7 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.24312.

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

pith.paper-citation-record.v1
2607.24312 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T18:32:14.529187Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

38 of 38 outbound references displayed

verified exact0
verified fuzzy0
unresolved38
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malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 054b1520-fd79-4df5-a9db-698e54b73515 · outbound

This paper cites Docred: A large-scale document-level relation extraction dataset,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Docred: A large-scale document-level relation extraction dataset,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.157159Z

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Unavailable: canonical work link unavailable.

Observation 7aee8e49-52d3-45a5-b298-e4faa1e545c6 · outbound

This paper cites Double graph based reasoning for document- level relation extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Double graph based reasoning for document- level relation extraction,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.240921Z

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Observation 5f85eb67-efa3-4f98-9679-4cf7036572f9 · outbound

This paper cites Augmenting neural networks with first-order logic,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Augmenting neural networks with first-order logic,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.300486Z

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Observation 4bd085d1-1c83-4952-a391-4060db178b9e · outbound

This paper cites Document-level relation extraction with adaptive thresh- olding and localized context pooling,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Document-level relation extraction with adaptive thresh- olding and localized context pooling,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.388755Z

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Observation 4e9c5eaf-2877-45c8-b131-ad7a33bbc371 · outbound

This paper cites Learning logic rules for document- level relation extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Learning logic rules for document- level relation extraction,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.455892Z

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Observation 5466620f-638f-4487-87c3-f34737e73996 · outbound

This paper cites Boosting document-level relation extraction by mining and injecting logical rules,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Boosting document-level relation extraction by mining and injecting logical rules,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.563454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd50921d-a3af-4c89-8073-69a7834a218b · outbound

This paper cites Towards better document-level relation extrac- tion via iterative inference,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Towards better document-level relation extrac- tion via iterative inference,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.663751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 361f8893-0505-48ca-b288-ca24ec8d749f · outbound

This paper cites Revisiting relation extraction in the era of large language models,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Revisiting relation extraction in the era of large language models,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.774978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc763048-c144-4dbd-9065-9e58cbb8eca2 · outbound

This paper cites Large language models for generative information extraction: A survey,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Large language models for generative information extraction: A survey,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.866095Z

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Unavailable: canonical work link unavailable.

Observation ed6615a3-3081-4a1a-a929-4748254ac2c3 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Reflexion: Language agents with verbal reinforcement learning,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:11.963283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6aeda523-3577-4488-9f3e-860196bc8999 · outbound

This paper cites Minillm: Knowledge distillation of large language models,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Minillm: Knowledge distillation of large language models,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.059173Z

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Observation 99f37db4-8aaa-4417-bf62-b478b0d0b4a0 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.136815Z

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Observation 4230ecda-0c51-4f08-b6a0-2b07e1bdfe07 · outbound

This paper cites En- tity structure within and throughout: Modeling mention dependencies for document-level relation extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models En- tity structure within and throughout: Modeling mention dependencies for document-level relation extraction,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.222049Z

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Observation 5d54ea59-eef2-4b79-b3fc-d49a1d389d47 · outbound

This paper cites Document-level Relation Extraction as Semantic Segmentation.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Document-level Relation Extraction as Semantic Segmentation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.311471Z

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Observation 0d5eef42-7741-44e4-a6f7-9486eb60f132 · outbound

This paper cites Dreeam: Guiding attention with evidence for improving document-level relation extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Dreeam: Guiding attention with evidence for improving document-level relation extraction,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.399702Z

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Observation 4f5393cf-bfa8-41d3-8d79-06d17fbc2eec · outbound

This paper cites End-to-end learning of logical rules for enhancing document-level relation extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models End-to-end learning of logical rules for enhancing document-level relation extraction,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.497990Z

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Observation 0e87844e-5605-46e3-a46f-222d2276c14e · outbound

This paper cites Rapl: A relation-aware prototype learning ap- proach for few-shot document-level relation extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Rapl: A relation-aware prototype learning ap- proach for few-shot document-level relation extraction,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.559379Z

Source-reported events for the cited work

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Observation c78a91f2-fa97-4692-a0f7-9fa88e6c889c · outbound

This paper cites Ptr: Prompt tuning with rules for text classification,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Ptr: Prompt tuning with rules for text classification,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.643915Z

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Observation 8d50a626-7e93-4e2a-9fd7-77fcbee9fb02 · outbound

This paper cites AutoRE: Document-Level Relation Extraction with Large Language Models.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models AutoRE: Document-Level Relation Extraction with Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.737324Z

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Observation 2e2f6ac3-eb4f-4a9d-bb24-05536ef717cb · outbound

This paper cites Consistency guided knowledge retrieval and denoising in llms for zero-shot document-level relation triplet extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Consistency guided knowledge retrieval and denoising in llms for zero-shot document-level relation triplet extraction,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.800623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5be99e72-8625-4df4-aeff-24a35bec1a5f · outbound

This paper cites Semi-automatic data en- hancement for document-level relation extraction with distant supervision from large language models,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Semi-automatic data en- hancement for document-level relation extraction with distant supervision from large language models,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:12.911440Z

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Unavailable: canonical work link unavailable.

Observation 2075f328-0492-4533-b96c-3bab66cc0432 · outbound

This paper cites Gpt-re: In-context learning for relation extraction using large language models,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Gpt-re: In-context learning for relation extraction using large language models,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.017810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb7c0001-4d9f-4f9d-83a3-7b9a7ad8a0e9 · outbound

This paper cites Prompt- free and efficient few-shot learning with language mod- els,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Prompt- free and efficient few-shot learning with language mod- els,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.095417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7443864a-da7c-476e-a791-eb3912b82837 · outbound

This paper cites Self-refine: Iterative refinement with self- feedback,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Self-refine: Iterative refinement with self- feedback,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.161637Z

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Unavailable: canonical work link unavailable.

Observation 738a34fb-e3db-42d8-ab5a-9004899d9ba2 · outbound

This paper cites Chain-of-verification reduces hallucination in large language models,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Chain-of-verification reduces hallucination in large language models,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.274872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 652b390e-a5d3-4e57-bab0-aa86139aaff3 · outbound

This paper cites Document-level relationship extraction by bidirectional constraints of beta rules,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Document-level relationship extraction by bidirectional constraints of beta rules,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.389810Z

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Observation 35276ffa-0f0b-478f-b80c-62e368e1c2e8 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Distilling the Knowledge in a Neural Network

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.487663Z

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Observation c6b6df9e-97be-4b0b-9121-051038861503 · outbound

This paper cites Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.579475Z

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Observation 0e216e29-f2b7-4a78-9a43-910d9ec90eff · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Constitutional AI: Harmlessness from AI Feedback

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.674829Z

Source-reported events for the cited work

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Observation df7009c1-0754-4ae9-ad3a-ed0976c9f2ab · outbound

This paper cites Proximal Policy Optimization Algorithms.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Proximal Policy Optimization Algorithms

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.775297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cd3c060-6734-4696-b831-32fb4f19432e · outbound

This paper cites Training language models to follow instructions with human feedback.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Training language models to follow instructions with human feedback

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.863146Z

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Unavailable: canonical work link unavailable.

Observation dff8a574-27b3-439a-835e-6567cea128d2 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:13.979180Z

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Observation f27b3b5c-1f44-48d1-aebb-9bb7a74674eb · outbound

This paper cites Let’s verify step by step,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Let’s verify step by step,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:14.062995Z

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Unavailable: canonical work link unavailable.

Observation 19d0a232-a0e8-4d4c-a26e-bec1f8b6cc7c · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:14.153131Z

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Observation eeaa2536-4fc8-443f-b345-835abaaa9a0c · outbound

This paper cites Large language models cannot self-correct reasoning yet,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Large language models cannot self-correct reasoning yet,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:14.262503Z

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Observation 4563db61-dad8-4807-a5c1-abf47b8254dc · outbound

This paper cites Refining chatgpt for document-level relation extraction: a multi- dimensional prompting approach,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Refining chatgpt for document-level relation extraction: a multi- dimensional prompting approach,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:14.342582Z

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Observation a48d802e-dbb9-4f12-93b5-c737a26e2aad · outbound

This paper cites LLM with Relation Classifier for Document-Level Relation Extraction.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models LLM with Relation Classifier for Document-Level Relation Extraction

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:14.433607Z

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Unavailable: canonical work link unavailable.

Observation 047f3792-5d90-40c2-ba49-15b224927a37 · outbound

This paper cites Revisiting docred-addressing the false negative prob- lem in relation extraction,.

CONSISTRE: A Unified Consistency-Aware Framework for Document-Level Relation Extraction with Large Language Models Revisiting docred-addressing the false negative prob- lem in relation extraction,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-31T18:32:14.529187Z

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Pith citing papers

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