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Paper Citation Record · LEDGER

Resurrecting Recurrent Neural Networks for Long Sequences

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2303.06349.

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

pith.paper-citation-record.v1
2303.06349 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:39:46.997865Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

43
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cac50261-77a3-497f-8254-d135f042bfe4 · inbound

Retentive Network: A Successor to Transformer for Large Language Models cites this paper.

Retentive Network: A Successor to Transformer for Large Language Models Resurrecting Recurrent Neural Networks for Long Sequences

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T20:29:59.886181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-11T20:29:59.633357Z digest=sha256:bb0e6f71e4f0924e7ae0ea63ffb5a511a2fea92d7af11c1c1b8df9ecc9d65354

Observation ce98f525-b304-4c09-adf3-bb09c72f19be · inbound

LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding cites this paper.

LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding Resurrecting Recurrent Neural Networks for Long Sequences

Reference 109

Resolution
verified exact
arxiv_id, observed 2026-05-12T20:22:10.673251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-12T20:22:10.482509Z digest=sha256:192ff8f00ed7e5549df53076aa5f0781f57297d98cfeff777fe99a44282eafb9

Observation ab224967-1657-4ec9-95cb-60effefa0f98 · inbound

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory cites this paper.

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory Resurrecting Recurrent Neural Networks for Long Sequences

Reference 19

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unresolved
no resolver link, observed 2026-08-08T23:49:09.446301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T23:49:09.446301Z digest=sha256:8cb3965f593aca98e2bd53a0d3f7bda5c7c348f939d7409faed83a21d909932e

Observation 8dc5cc42-3b6b-4639-8509-fbab59e8cf3b · inbound

L2RU: a Structured State Space Model with prescribed L2-bound cites this paper.

L2RU: a Structured State Space Model with prescribed L2-bound Resurrecting Recurrent Neural Networks for Long Sequences

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-22T22:42:13.726748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-22T22:37:32.448805Z digest=sha256:f7a81981f16a1db3b71cab109e5b8134d92e76d939f90597030eba4640601382

Observation 7f9f91c7-d205-4289-af5a-fff2cb27ab47 · inbound

Quantifying Memory Utilization with Effective State-Size cites this paper.

Quantifying Memory Utilization with Effective State-Size Resurrecting Recurrent Neural Networks for Long Sequences

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-16T05:58:23.376046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:58:23.376046Z digest=sha256:f5adf9abec0db843d76e60e99e6df16e8982c6b9913418ab4b7005fa23a1bf25

Observation 36879a81-9801-445d-a23f-b783110e1389 · inbound

An Empirical Study on Prompt Compression for Large Language Models cites this paper.

An Empirical Study on Prompt Compression for Large Language Models Resurrecting Recurrent Neural Networks for Long Sequences

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-16T10:39:46.997865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:39:46.997865Z digest=sha256:fbf8da77428204ac38c4591db7334cd3d5cad92b4c0f1d61966a48dea84e31dc

Observation 6e4a896a-ebc8-4b1c-8bcd-cd275420e6cb · inbound

Relative Overfitting and Accept-Reject Framework cites this paper.

Relative Overfitting and Accept-Reject Framework Resurrecting Recurrent Neural Networks for Long Sequences

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T22:16:04.875904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:16:04.875904Z digest=sha256:6c7cc098832b34b2a38dca142d59fc37f09e1129014c2c015431f734782bc8a8

Observation 6006f1e1-4b2b-43e4-82f9-dcc8d0ad8aff · inbound

Overflow Prevention Enhances Long-Context Recurrent LLMs cites this paper.

Overflow Prevention Enhances Long-Context Recurrent LLMs Resurrecting Recurrent Neural Networks for Long Sequences

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T22:12:58.767596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:12:58.767596Z digest=sha256:fe7078c10d44a21f69df7377b0a0c4fb119225e311d0614c88221700b0f2143c

Observation 1f7d8887-8000-459d-a1f3-014ab2de6d97 · inbound

Block-Biased Mamba for Long-Range Sequence Processing cites this paper.

Block-Biased Mamba for Long-Range Sequence Processing Resurrecting Recurrent Neural Networks for Long Sequences

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-15T21:49:30.439548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:49:30.439548Z digest=sha256:e40b2934e88fd40513d5da3f487fbb1b5d9eee5176f40dcaada129adfa624a1b

Observation c4b344d7-2a02-4d2c-8cbe-5b654b71387a · inbound

Bi-directional Recurrence Improves Transformer in Partially Observable Markov Decision Processes cites this paper.

Bi-directional Recurrence Improves Transformer in Partially Observable Markov Decision Processes Resurrecting Recurrent Neural Networks for Long Sequences

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T21:01:22.792509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:01:22.792509Z digest=sha256:ba28c3de407227c756cf0f1fddf6cd5ea2bd41a7f16d3f7678c8d73054a121f1

Observation caab8c05-60db-45b6-96f1-b1f50c6e58b0 · inbound

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models cites this paper.

MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models Resurrecting Recurrent Neural Networks for Long Sequences

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T14:08:11.477758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:08:11.477758Z digest=sha256:2fd9d2c2193c977d9a94611fe132cc8803082854d8515c0e2a984aa9b2e9b576

Observation 66db41c9-10aa-4ee0-b226-8083178a6391 · inbound

SiLIF: Structured State Space Model Dynamics and Parametrization for Spiking Neural Networks cites this paper.

SiLIF: Structured State Space Model Dynamics and Parametrization for Spiking Neural Networks Resurrecting Recurrent Neural Networks for Long Sequences

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:07:15.254503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T11:05:05.783726Z digest=sha256:68ee3ebaf3ec3b743146e4bcb22ed7bb3396f13a89bfcfc7bdafb998676bfe68

Observation 46de0cee-fe64-45a8-a0c2-e61b5445fbee · inbound

mGRADE: Minimal Recurrent Gating Meets Delay Convolutions for Lightweight Sequence Modeling cites this paper.

mGRADE: Minimal Recurrent Gating Meets Delay Convolutions for Lightweight Sequence Modeling Resurrecting Recurrent Neural Networks for Long Sequences

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T05:52:06.818812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-19T05:51:07.108143Z digest=sha256:e0531c8710b323c45ee0f9e4e18bfa569f69f574b05f9696795abd87eed8ee7b

Observation e9aeb0b7-13da-4852-a0d2-5725dd2e16d2 · inbound

Scalable Memristive-Friendly Reservoir Computing for Time Series Classification cites this paper.

Scalable Memristive-Friendly Reservoir Computing for Time Series Classification Resurrecting Recurrent Neural Networks for Long Sequences

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:41:10.526571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T01:10:45.859345Z digest=sha256:fe35ef9a485cd3969f2fd3673ec5974281c852ed9f016b9c4c3786dd1018e9e5

Observation 5ae67641-f2a3-4b72-aae5-c7466aa54696 · inbound

Parallel Scan Recurrent Neural Quantum States for Scalable Variational Monte Carlo cites this paper.

Parallel Scan Recurrent Neural Quantum States for Scalable Variational Monte Carlo Resurrecting Recurrent Neural Networks for Long Sequences

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-14T17:42:32.349333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-14T17:39:47.634924Z digest=sha256:b34d43fa97bcf5023ec7670031e9032d04fd040a13252a46f3ec4e5df948add4

Observation eb4c1dc6-b1b3-4c29-945d-0ebcb5911f0f · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Resurrecting Recurrent Neural Networks for Long Sequences

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:09:07.283213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-20T22:07:34.292536Z digest=sha256:b6cd2424a9f2ba6e4c0e8669215ec38d776f0a958894582bcec465269b2756dd

Observation ddfce801-466d-41a2-b8d3-3d518e7f532a · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Resurrecting Recurrent Neural Networks for Long Sequences

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:05:46.354431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T22:21:16.608148Z digest=sha256:15a16653707aa9e2658e0e958953e8aea8be346e7c787266a01e2a5ed4651f6a

Observation f7f4d150-1dbf-47d4-8cc6-d656cd16af1f · inbound

Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning cites this paper.

Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning Resurrecting Recurrent Neural Networks for Long Sequences

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-06-30T14:44:45.414595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-30T14:36:20.864181Z digest=sha256:4bc7af6221964a373e7f69fe7f0ac61543fab804b02c3486b64f1f69a3a217e1

Observation 6ed5995c-3a39-4779-a151-65b108406d57 · inbound

Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning cites this paper.

Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning Resurrecting Recurrent Neural Networks for Long Sequences

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-12T16:06:03.674959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T16:06:03.674959Z digest=sha256:507f8f518550aeee01183735381ff03dd45fc6203a71f908d4d39bba4df11498

Observation 1273b7c3-6014-471a-9078-1ab59d6ef817 · inbound

Free Parametrization of L_2-Bounded Structured State-Space Controllers for Nonlinear Control with Stability Guarantees cites this paper.

Free Parametrization of L_2-Bounded Structured State-Space Controllers for Nonlinear Control with Stability Guarantees Resurrecting Recurrent Neural Networks for Long Sequences

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-06-27T12:10:53.844589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-27T12:08:57.506333Z digest=sha256:ec18b9cf94d83e84823fad3b84cb0df1d75063fa3ffdebbb02a9989c136a93b8

Observation 908aaf08-db1a-4296-ad6a-1b56f4da9b4b · inbound

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement cites this paper.

Don't Listen to Me: A Lightweight, Low-Latency Model for Own-Voice Cancellation in Far-Field Speech Enhancement Resurrecting Recurrent Neural Networks for Long Sequences

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:29:51.718429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-26T06:49:46.425849Z digest=sha256:0398d43d40c3a262486136c7cd85fdaa3e649f89b86cde3ab3b670b8ef1af0d1

Observation e20879da-abe8-4a52-9875-4630e7364d98 · inbound

Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns cites this paper.

Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns Resurrecting Recurrent Neural Networks for Long Sequences

Reference 16

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verified exact
arxiv_id, observed 2026-07-04T17:29:59.831983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-25T23:43:20.900414Z digest=sha256:e73c265428a243a28f0d3a7e70a30d8f4edba4cfb4dd2907ee40c4decfa48c30