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Paper Citation Record · LEDGER

Multi-Relation Extraction in Entity Pairs using Global Context

As of 14 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.22926.

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

pith.paper-citation-record.v1
2507.22926 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:49:32.380008Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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 exact18
  • verified fuzzy17
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 447e52de-5141-4825-8576-879641d60cd6 · outbound

This paper cites Relation Extraction : A Survey.

Multi-Relation Extraction in Entity Pairs using Global Context Relation Extraction : A Survey

Reference 1

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unresolved
no resolver link, observed 2026-08-06T14:49:32.144114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:49:32.144114Z digest=sha256:78b2af789c9778c4976feb51f1090faaeb9705e44a76ff0ad76c9a9645851eac

Observation e6350dbd-db38-476e-aa92-6fcf56e922fd · outbound

This paper cites A Comprehensive Survey of Document-level Relation Extraction (2016-2023).

Multi-Relation Extraction in Entity Pairs using Global Context A Comprehensive Survey of Document-level Relation Extraction (2016-2023)

Reference 2

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no resolver link, observed 2026-08-06T14:49:32.150626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:49:32.150626Z digest=sha256:315f20daf8c77cd354849e164fbe7db0184d39141d55a390efd96ed42c798402

Observation 111853d6-a90c-4bf8-a4cc-923960300e3f · outbound

This paper cites A comprehensive survey on relation extraction: Recent advances and new frontiers,.

Multi-Relation Extraction in Entity Pairs using Global Context A comprehensive survey on relation extraction: Recent advances and new frontiers,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.255825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.156697Z digest=sha256:c7859654b870eac231ef9f26df59284b49d6ad50c7d0a5b5bd1fe78d27174c02

Observation bd6f5089-c5d2-4222-bacf-7c18eea77497 · outbound

This paper cites Dual-channel and hierarchical graph convolu- tional networks for document-level relation extraction,.

Multi-Relation Extraction in Entity Pairs using Global Context Dual-channel and hierarchical graph convolu- tional networks for document-level relation extraction,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.240061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.163174Z digest=sha256:f3ccc55d8aea77acbfafdc580203945c76348252ea38d7efc9f38e314d253191

Observation 920430ea-4823-4bd1-8c62-9db64b504dfa · outbound

This paper cites Document- level relation extraction with global and path dependencies,.

Multi-Relation Extraction in Entity Pairs using Global Context Document- level relation extraction with global and path dependencies,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.224853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.169877Z digest=sha256:e82be52c8b202950304df19434a2409e0ea2300dcededf3c11b88000e6b70c1e

Observation 729a9ce9-29b7-4d81-840d-b88ed22930c3 · outbound

This paper cites Corex: Document-level relation extraction framework with consistent two-hop reasoning and evidence sen- tence prediction,.

Multi-Relation Extraction in Entity Pairs using Global Context Corex: Document-level relation extraction framework with consistent two-hop reasoning and evidence sen- tence prediction,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.209439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.175777Z digest=sha256:13b6f927f18edcda59b0557c3a48f36f00c144901b594dcbeaec1cd4c51f9bae

Observation dc4a23b9-3fb4-40e8-8d87-6db59a539633 · outbound

This paper cites Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network.

Multi-Relation Extraction in Entity Pairs using Global Context Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.933478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.182645Z digest=sha256:e9620530ca15db9b19f1d78e5502d6994c5aa33c3fe294b76b1cbc3f6f2de320

Observation 1464c426-158b-49e8-a8b7-812fe8b18ca2 · outbound

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

Multi-Relation Extraction in Entity Pairs using Global Context Document-level relation extraction with adaptive thresholding and localized context pooling,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.194195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.188729Z digest=sha256:b34bd4c1412d05f3da515ce327cc3ef71aff9581713c71573d9e42707b3a35b4

Observation 17361b7d-df92-47dd-aa3d-e15b489eea17 · outbound

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

Multi-Relation Extraction in Entity Pairs using Global Context Entity structure within and throughout: Modeling mention dependencies for document-level relation extraction,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.178391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.194115Z digest=sha256:465b0856740e9294b9612dca56bcff45d5fe36f5fed4ca753c09c49be84d2101

Observation aa9fbbde-273a-4038-b602-ab4c4a8732da · outbound

This paper cites Relation classification via convolutional deep neural network,.

Multi-Relation Extraction in Entity Pairs using Global Context Relation classification via convolutional deep neural network,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.162396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.200553Z digest=sha256:64e1dda344653b38e6ed5b80abdc0d5df9b1f9cdacae1bd178fff3947480f19a

Observation 2be84594-edee-4eec-9488-8f0cf15dd152 · outbound

This paper cites Bidirectional recurrent con- volutional neural network for relation classification,.

Multi-Relation Extraction in Entity Pairs using Global Context Bidirectional recurrent con- volutional neural network for relation classification,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.146717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.205896Z digest=sha256:a1ded7bb8f7da9594958445ecafc539558b4cd20b86070bcb0266ca0a08b01f5

Observation 8a0b2ad7-abd0-46c7-9254-313eeec136f6 · outbound

This paper cites PRGC: Potential Relation and Global Correspondence Based Joint Relational Triple Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context PRGC: Potential Relation and Global Correspondence Based Joint Relational Triple Extraction

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.909787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.212698Z digest=sha256:0c9c2b6169f8978d106399fe4996b1cfa82072291ea89f1e8901d12a53b41f78

Observation 3c8e2167-59e9-4970-a276-eece13be6784 · outbound

This paper cites DocRED: A Large-Scale Document-Level Relation Extraction Dataset.

Multi-Relation Extraction in Entity Pairs using Global Context DocRED: A Large-Scale Document-Level Relation Extraction Dataset

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.883227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.217970Z digest=sha256:12908641b83253b79cb44f077591dcb54a0d70bcaea675a3d02125c6a15ce787

Observation ea32cbf8-8674-4581-8a21-fdb2d759ba4a · outbound

This paper cites an unresolved cited work.

Multi-Relation Extraction in Entity Pairs using Global Context Unresolved cited work

Reference 14

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unresolved
raw_fallback, observed 2026-08-06T14:49:33.129797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.223681Z digest=sha256:89be1524ed9f9ab50b8a860288f0a49e223e99c5fce25fc5e0c397b48880d403

Observation 337a582e-3c97-4f8a-9191-87b5f85288db · outbound

This paper cites Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs.

Multi-Relation Extraction in Entity Pairs using Global Context Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:32.228756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:49:32.228756Z digest=sha256:7a7bafbda6909a7a9c92e2ecd04d110698956257b287bac539c63752707c81ec

Observation 9ce7be7e-93aa-4814-859c-16682c911812 · outbound

This paper cites Distant Supervision for Relation Extraction beyond the Sentence Boundary.

Multi-Relation Extraction in Entity Pairs using Global Context Distant Supervision for Relation Extraction beyond the Sentence Boundary

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:32.234505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:49:32.234505Z digest=sha256:8964b6a0c41b0021a8ac1062d77dc085dbcfd84d180cf1065cf2dc03e6db759c

Observation e283e6e3-3df9-4203-86c7-2fca5825eade · outbound

This paper cites Reasoning with Latent Structure Refinement for Document-Level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context Reasoning with Latent Structure Refinement for Document-Level Relation Extraction

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.816686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.239890Z digest=sha256:f77b57d15b61e37638f92b4cf2f788e265b156eb3a82ad7b3092f8e6ba37de14

Observation 0621930c-5ba2-44c1-a9b2-38e62e6f3225 · outbound

This paper cites Global-to-Local Neural Networks for Document-Level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context Global-to-Local Neural Networks for Document-Level Relation Extraction

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.789599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.245545Z digest=sha256:3aea08472694beeafc00b7404b72572f59c9aef35dfdb1722ecca6d0732cc0ea

Observation 6dd117f2-a88b-4eff-9a2a-81b31d6a1ff7 · outbound

This paper cites Double Graph Based Reasoning for Document-level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context Double Graph Based Reasoning for Document-level Relation Extraction

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.765673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.251015Z digest=sha256:09c20acedc0218710abe23ff02e2e342dd8250385c22be252d03223f5552e18a

Observation 9b5e35ba-f0f8-44a1-a062-a8b78244e811 · outbound

This paper cites Graph enhanced dual attention network for document-level relation extraction,.

Multi-Relation Extraction in Entity Pairs using Global Context Graph enhanced dual attention network for document-level relation extraction,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.114391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.256585Z digest=sha256:66ba7709db6628c3ba231f809f88e57fe738d17eee073687c611d0f2dad13b36

Observation 89d0ddc1-4049-4220-b78a-079926b1d629 · outbound

This paper cites Document-level relation extraction with dual-tier het- erogeneous graph,.

Multi-Relation Extraction in Entity Pairs using Global Context Document-level relation extraction with dual-tier het- erogeneous graph,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.099477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.261760Z digest=sha256:c6ee301534599f2d727459e9987605c6e21598181df1a3ac4b2617ba31875255

Observation 834592e8-48f6-46dc-9918-f2bfd8afea4f · outbound

This paper cites Mrn: A locally and globally mention-based reasoning network for document- level relation extraction,.

Multi-Relation Extraction in Entity Pairs using Global Context Mrn: A locally and globally mention-based reasoning network for document- level relation extraction,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.083545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.266834Z digest=sha256:5ba358da163953696834eda28a2aeeb5d203caf272094c2112995077c37a0831

Observation f6709b6b-3d7e-4ca3-b6ab-720013e603a1 · outbound

This paper cites Document-level relation extrac- tion with reconstruction,.

Multi-Relation Extraction in Entity Pairs using Global Context Document-level relation extrac- tion with reconstruction,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.066335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.272893Z digest=sha256:5d6daee13c1213f197c8973bc5a3934e25de260bcc436c00a7132cdf35512a58

Observation 3ff1020a-3cb5-4f85-99dd-4f9457eae8ca · outbound

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

Multi-Relation Extraction in Entity Pairs using Global Context Entity structure within and throughout: Modeling mention dependencies for document-level relation extraction,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.049808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.278318Z digest=sha256:35174f1e45724072d4773ec0893b1f26d4650f863de9c3f73898bee28fb78ce8

Observation d5552fcc-bfdd-443e-bfaf-db1754133ff3 · outbound

This paper cites Learning Logic Rules for Document-level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context Learning Logic Rules for Document-level Relation Extraction

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.741277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.283502Z digest=sha256:c2a3c6db39f35ff613d354879aab9632e53c804640aaaaeb7524e0963daad658

Observation cda44d1c-490c-4dce-86bf-54698a5b881f · outbound

This paper cites Modular Self-Supervision for Document-Level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context Modular Self-Supervision for Document-Level Relation Extraction

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.717615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.288592Z digest=sha256:dae76d121f66af6930119481b7d5ca8e7341e5e49ed9ff8c7d8a88affb4c1203

Observation f71e7bbd-f5cf-4a28-a630-4fbdcb958253 · outbound

This paper cites Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context Revisiting DocRED -- Addressing the False Negative Problem in Relation Extraction

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.694723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.294059Z digest=sha256:e208ad9fce8bd59dd31f738ebb51e903788b31b9c0107b02888e8110340c9f5b

Observation 0f76dc9f-f335-473b-bd0b-813555293632 · outbound

This paper cites Rebel: Re- inforcement learning via regressing relative rewards,.

Multi-Relation Extraction in Entity Pairs using Global Context Rebel: Re- inforcement learning via regressing relative rewards,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.033845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.299761Z digest=sha256:65e9ce9677952ecf171c9ed18c9ab96ae8f6c2cece544d924fdad86177563315

Observation 5ac8aa7b-e41c-4b37-9811-9f306f65876c · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

Multi-Relation Extraction in Entity Pairs using Global Context BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:32.305476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:49:32.305476Z digest=sha256:d36f9e0b0fab38ec6799ca2f9bd45ae7fc892ae7fb52f96a188a0c3b71e52e60

Observation af290ae7-52b4-4686-a729-69b6c9a4a059 · outbound

This paper cites SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.652045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.310801Z digest=sha256:e02b22abfa5d8abe57afc3f550aa2b62721f7173134c92aca48eddabe54c903a

Observation 8a3eec53-4920-4a51-ae7f-26ffba656bf8 · outbound

This paper cites Discriminative Reasoning for Document-level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context Discriminative Reasoning for Document-level Relation Extraction

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:32.316481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:49:32.316481Z digest=sha256:187f68751247446d1a5b5207546d55242b32a1149286b1e2172dd8bbe785f1c1

Observation bc3ec281-fb41-42dd-85a6-061ed74bab0b · outbound

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

Multi-Relation Extraction in Entity Pairs using Global Context Document-level Relation Extraction as Semantic Segmentation

Reference 32

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.610995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.321639Z digest=sha256:ef4c6a0228a97eab6b8fdbff331257c844580ebbda9d5f54d9a7a47e603c41a6

Observation de6906b0-2d1e-4b59-89c8-384d96f5e096 · outbound

This paper cites A Unified Positive-Unlabeled Learning Framework for Document-Level Relation Extraction with Different Levels of Labeling.

Multi-Relation Extraction in Entity Pairs using Global Context A Unified Positive-Unlabeled Learning Framework for Document-Level Relation Extraction with Different Levels of Labeling

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.585789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.327905Z digest=sha256:81f7a744fec2f83e2c113aac2e27658f1449dd3e21b9f5341eea45ebb45522df

Observation 462d1ebc-c379-4ed7-8199-54306af8ce9d · outbound

This paper cites Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation.

Multi-Relation Extraction in Entity Pairs using Global Context Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.559508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.333155Z digest=sha256:620c9a4e7abf88f67583b004575fc4089b67504394c3600c4a8b0188c60a8d8b

Observation f5ca800d-1022-4744-b17b-a5b3451f902a · outbound

This paper cites SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.530843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.340723Z digest=sha256:b4ea9d24d7e8adf2112fa678c56af8a1a9a15d32989e44a8dc8498c9d45de16a

Observation 9bf4e08a-9dce-4645-9409-95a994970296 · outbound

This paper cites DREEAM: Guiding Attention with Evidence for Improving Document-Level Relation Extraction.

Multi-Relation Extraction in Entity Pairs using Global Context DREEAM: Guiding Attention with Evidence for Improving Document-Level Relation Extraction

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.506799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.346539Z digest=sha256:063fe8ad71768191d615a60f1ee3decd89c302af0b2df698930d09c4d3815602

Observation f35aa0a6-4d59-49b4-b2cf-8ebb640df2a2 · outbound

This paper cites Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion.

Multi-Relation Extraction in Entity Pairs using Global Context Eider: Empowering Document-level Relation Extraction with Efficient Evidence Extraction and Inference-stage Fusion

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.483364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.352090Z digest=sha256:2d2878be11b3c54aa624716f24727f5530edfa300a4687b98cd5b68d0956b1b5

Observation fa95eac1-1672-4b4d-906c-a2459c4f5193 · outbound

This paper cites Enhancing document- level relation extraction by entity knowledge injection,.

Multi-Relation Extraction in Entity Pairs using Global Context Enhancing document- level relation extraction by entity knowledge injection,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.018430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.357467Z digest=sha256:9ae415d515e0f826144bad429335f6fdc2b6cafb1595a34c032de0e779038347

Observation ff537121-729f-42c3-835a-acc76c3a2b30 · outbound

This paper cites RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information.

Multi-Relation Extraction in Entity Pairs using Global Context RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.459572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.362320Z digest=sha256:ae80baf187ecccff5059d0494c43008e6f97391b71a2cef03939f1f8074091a8

Observation 09933673-ce70-4d25-ac5f-34eec1d32a65 · outbound

This paper cites Recon: relation extraction using knowledge graph context in a graph neural network,.

Multi-Relation Extraction in Entity Pairs using Global Context Recon: relation extraction using knowledge graph context in a graph neural network,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:33.001339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.368032Z digest=sha256:b420ef891c03731d35eefc55cedcd198239e4b6d80bc7739cded4c6d68fc4120

Observation 6b9e70f2-cbee-4c54-b16f-7821c422e84d · outbound

This paper cites Injecting Knowledge Base Information into End-to-End Joint Entity and Relation Extraction and Coreference Resolution.

Multi-Relation Extraction in Entity Pairs using Global Context Injecting Knowledge Base Information into End-to-End Joint Entity and Relation Extraction and Coreference Resolution

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:49:32.435399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.373231Z digest=sha256:19579a88e130f2720dc614423729806b66f9b492339dd614050fd808538d6345

Observation 5f28d807-ea8c-4ecc-ab4c-75475bbdf057 · outbound

This paper cites Revisit- ing document-level relation extraction with context-guided link prediction,.

Multi-Relation Extraction in Entity Pairs using Global Context Revisit- ing document-level relation extraction with context-guided link prediction,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:32.984797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T14:49:32.380008Z digest=sha256:ac41cc4240288fbd0f7193938c5416e2c64f8a3a7da86d041cacbe79672c7014

Pith citing papers

No inbound Pith citation observations are available.