Pith. sign in

Paper Citation Record · LEDGER

A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.15026.

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

pith.paper-citation-record.v1
2410.15026 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:55:20.901732Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T22:49:30.227190Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c3d496e4-1776-42e9-8659-86f5591d759e · inbound

A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation cites this paper.

A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T17:55:20.901732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:55:20.901732Z digest=sha256:314e04809cba8959197b753c46217bdcdcaf38a70347ea4c2e855625b707904f

Observation 53f067ed-11c4-42f2-af8e-09c91b720fca · inbound

Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction cites this paper.

Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T17:55:18.044764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:55:18.044764Z digest=sha256:26f33681f6ec16528bb62011f7cb55aa49bbbcf39e30b684aa081f6f769bab8a

Observation 637ade43-10c2-40c6-9b0d-c1c7714d1989 · inbound

Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs cites this paper.

Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T17:23:20.658740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:23:20.658740Z digest=sha256:f7a2c9148ecb3d4069f3bdbcacbffb472aacc3323bb4e7f62bc4bc35ea1f0295

Observation 487adaa6-8869-4ad3-a926-b8cb73da6786 · inbound

Optimizing Gesture Recognition for Seamless UI Interaction Using Convolutional Neural Networks cites this paper.

Optimizing Gesture Recognition for Seamless UI Interaction Using Convolutional Neural Networks A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-12T14:10:42.378865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:10:42.378865Z digest=sha256:e06494be82faa4995c7f8e584f9ff43ce6194573aea7e13841cca5de1370e8ea

Observation f71d9240-02f5-4034-9eaf-c33c3bcf7df2 · inbound

Enhancing Few-Shot Learning with Integrated Data and GAN Model Approaches cites this paper.

Enhancing Few-Shot Learning with Integrated Data and GAN Model Approaches A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T13:01:12.785775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:01:12.785775Z digest=sha256:f866dd6d1288c58df2f92555c3ab510c42e56f3362b57553af9c08ad6f3d40e2

Observation 887c7f6d-5753-4785-97a3-9afdf7a437ed · inbound

Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data cites this paper.

Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-12T11:03:15.164929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:03:15.164929Z digest=sha256:b6f586dcd37dad7d2223fe93d623ce70e68f6b8d050970a187d64539b95969af

Observation b3571ff7-b80e-41c0-8362-315702b650a4 · inbound

An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction cites this paper.

An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T23:46:09.696688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:46:09.696688Z digest=sha256:262e11ed9e4c9c8410a124e1bb118bb7f010b9d62e3a5a924673cddc51f4cb6f

Observation 90f992e6-c183-4547-8232-e8b441c7d3c9 · inbound

Leveraging Generative Adversarial Networks for Addressing Data Imbalance in Financial Market Supervision cites this paper.

Leveraging Generative Adversarial Networks for Addressing Data Imbalance in Financial Market Supervision A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-11T22:49:30.231927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T22:49:30.013653Z digest=sha256:be7ea90a24e0062df4aad11d1f6bc1c62193bfd55ffa9f75eae41bbf4dc20269