Paper Citation Record · LEDGER

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments

As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2501.07905.

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

pith.paper-citation-record.v1
2501.07905 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:34:09.643206Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

31 of 31 outbound references displayed

verified exact0
verified fuzzy16
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 79f05512-3497-4518-84d8-fee1f5f88f6d · outbound

This paper cites Finding structure in time,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Finding structure in time,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.188422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e0c0db79-9834-4ec1-a198-1b53b56c464e · outbound

This paper cites Recurrent neural network based language model,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Recurrent neural network based language model,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.164354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 812601b7-21da-4b6a-91cc-87a705938f31 · outbound

This paper cites Rnn++: A lightweight, optimized recurrent neural network for long sequences,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Rnn++: A lightweight, optimized recurrent neural network for long sequences,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.138876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dd83c137-9353-448f-a0c9-1b93b8a68bd7 · outbound

This paper cites Neural memory architectures for sequential decision-making,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Neural memory architectures for sequential decision-making,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.118809Z

Source-reported events for the cited work

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Observation 33f1421f-3b91-4075-8d9b-ba4f40e5dd26 · outbound

This paper cites Long short-term memory,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Long short-term memory,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.507450Z

Source-reported events for the cited work

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Observation 2cff26ee-4b29-42b8-acc2-0c058d4826ca · outbound

This paper cites Neural machine translation by jointly learning to align and translate,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Neural machine translation by jointly learning to align and translate,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.088528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0af03e4d-ac5f-44da-82d7-f266b79a28ed · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.519304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbbe348a-7d00-4aac-bace-d0153710f255 · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.525377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 509d927c-5ba5-470b-93f1-2516c7510f2d · outbound

This paper cites Attention is all you need,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Attention is all you need,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.530927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02cea7ef-a81c-412c-beba-bcf37fbf0a4d · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.535562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4809de5e-f98c-473e-820e-d6e05c658e96 · outbound

This paper cites Improving language under- standing by generative pre-training,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Improving language under- standing by generative pre-training,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.061872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b8800607-7e77-4798-adaf-fd46ef30ba2e · outbound

This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.545810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4322170-6a3d-4690-ab78-126615ccf8f4 · outbound

This paper cites Longformer: The Long-Document Transformer.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Longformer: The Long-Document Transformer

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.550899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32278cde-15c2-4169-bcb5-b4a31a6d073f · outbound

This paper cites Linformer: Self-Attention with Linear Complexity.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Linformer: Self-Attention with Linear Complexity

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.555543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4b796c8-a834-4096-888f-e632e68f0a6d · outbound

This paper cites Neural Turing Machines.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Neural Turing Machines

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.560465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 735b5004-056d-4c7b-bda1-0d1a118d873c · outbound

This paper cites Memory Networks.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Memory Networks

Reference 16

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Source-reported events for the cited work

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Observation 572576cd-d41e-44ff-972b-09b6c7666705 · outbound

This paper cites Hybrid computing using a neural network with dynamic external memory,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Hybrid computing using a neural network with dynamic external memory,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.043466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a211f44c-6b94-4843-8fe8-9f56801eb5f2 · outbound

This paper cites Hippo: Recurrent memory with optimal polynomial projections,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Hippo: Recurrent memory with optimal polynomial projections,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.029914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1afdbeea-720a-4560-9954-4dfcc7634dcd · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Efficiently Modeling Long Sequences with Structured State Spaces

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:09.581188Z

Source-reported events for the cited work

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Observation 06d1f448-3d44-454a-a4cd-d4a885c79b60 · outbound

This paper cites Learning Objective Functions Incrementally by Inverse Optimal Control.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Learning Objective Functions Incrementally by Inverse Optimal Control

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c7366ab9-7562-438a-a2ca-631c588d9d2b · outbound

This paper cites Hybrid memory networks for sequential data processing,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Hybrid memory networks for sequential data processing,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.016048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 11c17797-f31b-4631-8ac7-5f1779260290 · outbound

This paper cites CautionSuicide: A Deep Learning Based Approach for Detecting Suicidal Ideation in Real Time Chatbot Conversation.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments CautionSuicide: A Deep Learning Based Approach for Detecting Suicidal Ideation in Real Time Chatbot Conversation

Reference 22

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T20:34:09.733487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 472533a7-815d-4547-81e4-ed027d287f57 · outbound

This paper cites Synthformer: Beyond token-level self-attention,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Synthformer: Beyond token-level self-attention,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:10.001540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bd64005e-1c14-4955-bbd0-4522e7343038 · outbound

This paper cites Recurrent attention mechanisms for efficient long-sequence process- ing,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Recurrent attention mechanisms for efficient long-sequence process- ing,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:09.986405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8694e2e0-445c-4f92-b47d-2ed486c69b7e · outbound

This paper cites Dynamic memory transformers for efficient long-sequence model- ing,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Dynamic memory transformers for efficient long-sequence model- ing,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:09.968935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7d5fb4c5-1cb4-4fc6-9398-dbfdab4cb186 · outbound

This paper cites Characterization and Generation of 3D Realistic Geological Particles with Metaball Descriptor based on X-Ray Computed Tomography.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Characterization and Generation of 3D Realistic Geological Particles with Metaball Descriptor based on X-Ray Computed Tomography

Reference 26

Resolution: metadata mismatch; local_arxiv, observed 2026-08-10T20:34:09.710893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cff6f832-cbcb-4be9-a8a3-376d508030a6 · outbound

This paper cites Scaling structured state space models for long sequences,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Scaling structured state space models for long sequences,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:09.952423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ddd5ee28-fe73-49ec-bf5f-61ba7e179519 · outbound

This paper cites Compact state space models for efficient long-term dependencies,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Compact state space models for efficient long-term dependencies,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:09.937307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 15c3b640-75e4-4156-b351-63eba363a0a3 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 29

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Source-reported events for the cited work

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Observation f68be937-aa67-4132-97c5-1b5d034a4641 · outbound

This paper cites Switch transformers: Scaling models with mixture- of-experts layers,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Switch transformers: Scaling models with mixture- of-experts layers,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:09.919371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f294a326-3bd1-473c-a8b6-cf911c75aa04 · outbound

This paper cites Modular mixture of experts for efficient sequence modeling,.

Logarithmic Memory Networks (LMNs): Efficient Long-Range Sequence Modeling for Resource-Constrained Environments Modular mixture of experts for efficient sequence modeling,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:34:09.903884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.