Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:45:16.702498Z
Paper Citation Record · LEDGER
As of 20 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2506.23767.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:45:16.702498Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
80 of 80 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach , " * write output.state after.block = add.period write newline
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach European Journal of Operational Research 202(3):789--801, ISSN 0377-2217, ://dx.doi.org/https://doi.org/10.1016/j.ejor.2009.06.023
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Management Science 67(7):4004--4031
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach American Economic Review 97(2):159--165
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Journal of Financial Research 39(2):145--178
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach 2005 IEEE computer society conference on computer vision and pattern recognition (CVPR'05), volume 1, 539--546 (IEEE)
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Unresolved cited work
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach NIPS 2014 Workshop on Deep Learning, December 2014
Reference 16
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Optimization Challenges in Complex, Networked and Risky Systems, 269--281 (INFORMS)
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Contemporary Accounting Research 29(3):804--837
Reference 18
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Physica A: Statistical Mechanics and Its Applications 622:128886
Reference 19
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach NAACL-HLT (1) , 4171--4186 (Association for Computational Linguistics)
Reference 20
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Reference 21
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 0210--0215, ://dx.doi.org/10.23919/MIPRO.2018.8400040
Reference 22
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach ACM Computing Surveys 56(9):1--42
Reference 23
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Journal of Accounting and Economics 64(2):221--245, ISSN 0165-4101, ://dx.doi.org/https://doi.org/10.1016/j.jacceco.2017.07.002
Reference 24
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Observation 93ab11ee-6acd-416a-a16c-72c2cdc9b395 · outbound
Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach The European Journal of Finance 6(1):18--38
Reference 25
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Journal of Financial Economics 33(1):3--56, ISSN 0304-405X, ://dx.doi.org/https://doi.org/10.1016/0304-405X(93)90023-5
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Reference 27
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Comparative Economic Studies 53:511--534
Reference 28
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach ACM Computing Surveys (CSUR) 55(1):1--30
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Reference 30
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach The Llama 3 Herd of Models
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Neural Computing and Applications 29:343--358
Reference 32
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Similarity-based pattern recognition: third international workshop, SIMBAD 2015, Copenhagen, Denmark, October 12-14, 2015
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach The Journal of Finance 53(3):1111--1130
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Findings of the Association for Computational Linguistics: EMNLP 2020, 4163--4174
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Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Advances in neural information processing systems 30
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Observation 35ac2032-b5b6-45cd-8c8e-a375ab868277 · outbound
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Reference 59
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Observation ac4ca4b9-86d5-4b0d-8988-9cf1479518fd · outbound
Explainable AI for Comprehensive Risk Assessment for Financial Reports: A Lightweight Hierarchical Transformer Network Approach Thirty Fourth International Conference on Information Systems, Milan
Reference 60
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Observation ca988adc-8617-4d35-a7f6-020b4e9f7e96 · outbound
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Reference 61
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Reference 63
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Observation 2054f12f-2397-4748-b194-4968a2783d82 · outbound
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Reference 64
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Reference 65
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Observation 5493829e-33dd-45d1-9a78-64680f70ce56 · outbound
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Reference 66
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Observation 16b18542-d019-4e52-8433-067b0a213a00 · outbound
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Reference 67
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Observation 7e2da8d7-ce10-48f7-9440-8eac94114aa5 · outbound
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Reference 68
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