Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T11:04:10.873794Z
Paper Citation Record · LEDGER
As of 21 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:1908.09982.
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 2026-08-14T11:04:10.873794Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-23T19:42:24.122342Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T19:43:23.233823Z
53 of 53 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation d486de39-73c5-4862-ba25-50e24f91be8a · outbound
On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression write newline
Reference 1
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression URL: " 'urlintro :=
Reference 2
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression write newline
Reference 3
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Observation 54c2b060-1365-45d4-8a0f-0e9fde7aa603 · outbound
On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Neural Machine Translation by Jointly Learning to Align and Translate
Reference 4
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Observation 2371fb0b-4988-48a0-b96a-64dd9ca5b3f9 · outbound
On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 5
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Bowman, Gabor Angeli, Christopher Potts, and Christopher D
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 7
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 8
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 9
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 10
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 11
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Reference 12
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Gers, J\" u rgen A
Reference 13
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Observation 565f12c5-c2cd-4ad3-bda1-50a5c63990ae · outbound
On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Compressing Deep Convolutional Networks using Vector Quantization
Reference 14
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 16
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 17
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 18
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 19
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 20
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 21
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Learning to Prune Filters in Convolutional Neural Networks
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Reference 23
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 24
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 27
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 28
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
Reference 29
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Unresolved cited work
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On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini
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Reference 53
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