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Paper Citation Record · LEDGER

Multi-Relation Extraction in Entity Pairs using Global Context

As of 7 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 2026-08-07T06:34:17.273281+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

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:ff459f6ae47a9203910b163c41ff56a9225ea4bc71f64169da17fdc1451938d8

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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unresolved
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=sha256:27d434b769a9aad5862817f6ab47e8bc4e5b0cd6c4555b5fc96e202b3dcd024a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.156697Z digest=sha256:5fbe18437ca880b37436b5bdbb40864e8843d52526ef7442398a7c1b76819594

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.163174Z digest=sha256:fcefd25893ff443378c7baf4c5a4cd2582446bacc416f013887b422980e72137

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

Resolution
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.169877Z digest=sha256:4d2c21a7ea6ec6ceaa424e96cd66e0a39150577ccd461269d72d2de36dc42c38

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.175777Z digest=sha256:23aea65db53218ae99a61bbccce1496b8cb86ef206f3f76f41efb5e9398acb6c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.182645Z digest=sha256:1dfe3c42f30ecea243fe113444212b910635aa6b79b82b67e0f23eb5be25909f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.188729Z digest=sha256:acff6a457da26b01e5cf753cea9533fb5a824bbcf34d223081740893257f582b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.194115Z digest=sha256:f9477197d89c25889ea805a1c42e3d34ba37ea239e62e3bb65a1fd1b5a4d0c1e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.200553Z digest=sha256:2dbd973d287ed2fc8a03a42bcae9685058140a7fb2b36160c926cb249f363dbd

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.205896Z digest=sha256:9dba89fd284602c283c3a0dcb2edf5c721be14d99069a2361f5b6afd3e26e5db

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.212698Z digest=sha256:9bd77c092d6687cc95262bf370fde92c4d14a4c135b2f2aa1be428e09209d9c7

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.217970Z digest=sha256:d85341e6273af73b670447e54cf4a4140106ada6cf95f54268358b6b6c888513

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.223681Z digest=sha256:b1e1ce08f0e21f2c5ca1d588ee81e55a1521bc068b0bcac46a83624dd761396f

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:b8db9215f3964c4c00dc41e490ada11a42a5143c44d56d6e6068c19902cf0493

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=sha256:422336d5669c4c99fd431c6efa8369f3ab51d7207120247c76736b4d1aaaf5b4

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.239890Z digest=sha256:d12df0afb514f0faa628989fe737340a50775b9a2b0a8984c113c56f1c638456

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.245545Z digest=sha256:7628345a605501704905f8e9228904b8ca12dc506e189900dca45410e094ffe2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.251015Z digest=sha256:b217bf34f2a2a3285deca38247cbb44cbab08b3f0e4dbb183d83932e07e7711d

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.256585Z digest=sha256:13295e1edb04e5c16269e3063b45b73158cd37c82ebeefcfbbcb4f05130fbe73

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.261760Z digest=sha256:735bfa5e5e7dd0510d1ca3550a747f494e6dca68b7c380b77423bbdf71c0e0c5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.266834Z digest=sha256:3c494a1138bc33a0dc8aff4b33a443f5f865e372a2d6741b1205c01a89f6b843

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.272893Z digest=sha256:7c70124cce730ab772a580de04da1e9968fd3782164c5928182a8c9ffc4e4c03

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.278318Z digest=sha256:b14620de07e9882607e9f8d9c3625ce8b96fdcd7246d12737c96693e81758af7

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.283502Z digest=sha256:76727a3924b44dd4107fbc97bc5f1ff15fd9aaff822069bb35cb3623bb21877f

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.288592Z digest=sha256:a27108a6d19e598a2e8bcfe38b91749f32decd6da2c11348517a99ec95d0e835

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.294059Z digest=sha256:70cfa300b33b7af42e836821b1d04ae53a6771c98c07f55ebb3488a12e6f19e9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.299761Z digest=sha256:90ead9f00c6d3ab9a6b5027f9cbd54a0e5edf6f022b38d11343091ace8dcab6c

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:e7ffe6d0b6e1d964b7825ec3eda061f0dca1a541ae769a16d35f42434c97acd1

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.310801Z digest=sha256:734ebc09b478f2bd03f91859c93eae1af81b063947ae632e1a578b498b1d8e33

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:ea016e39b48c5cf78581c38f3df103c552c770460f90762e3fbfaf4465fd908a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.321639Z digest=sha256:57171b95403f3206bc16b224a98bc7cd365240e1604218996bc6fdc1501454ea

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.327905Z digest=sha256:3ae0215178953e5026e9aa815d7911064276630eb80b70a727dea92c879d7b51

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.333155Z digest=sha256:ad0158fdef99cef4cfa81c3b6c493b20a3d828918da4f5bb07c6f2100a90ddea

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.340723Z digest=sha256:3e7bfaab069344e4fd98e6806b2382dc74e8c2107e400642b3fadfc67154ca32

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.346539Z digest=sha256:0f77d3dc0d6325ba8f05a70d53ac30066f637ff36bd82a944694acfbc794c350

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.352090Z digest=sha256:caa7eed801100d52aa59c0fcca08485edcd77d9e0239f10ab566523f397093f4

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.357467Z digest=sha256:f2efdae13fd63457190d86060f9c4a47350cefa086eab79edb0e52e299841d0a

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.362320Z digest=sha256:02bd537e2851954125c6cd767687f471383eb0ac3086a0b1dd38dee52aca66f6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.368032Z digest=sha256:4297ea984c0af04c61d1a759496dca02e43a0157f5b42e00ace4eb556401e6e8

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.373231Z digest=sha256:4ddbfa885e9751710e02725ff9cb7e815e6e8fab60709514c95adb21a0d4e257

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T14:49:32.380008Z digest=sha256:9860bf64c9b306f9eb520029fd2293ea11af9112b2ef680c8740d5cd344aeff0

Pith citing papers

No inbound Pith citation observations are available.