Paper Citation Record · LEDGER

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting

As of 9 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.06128.

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

pith.paper-citation-record.v1
2506.06128 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:02:58.233008Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

14 of 14 outbound references displayed

verified exact3
verified fuzzy8
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71e8a8cc-9695-44ca-9537-c8ef8219df12 · outbound

This paper cites HGNET: A Hierarchical Feature Guided Network for Occupancy Flow Field Prediction.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting HGNET: A Hierarchical Feature Guided Network for Occupancy Flow Field Prediction

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-07T06:02:58.314266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a673c721-50df-49a8-9aac-67c3037cd043 · outbound

This paper cites Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T06:02:58.192274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a114ca8-cc39-4f70-b3ae-5b7e7a210ded · outbound

This paper cites Simple-bev: What really matters for multi-sensor bev perception? In 2023 IEEE International Conference on Robotics and Automation (ICRA), pages 2759–2765.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Simple-bev: What really matters for multi-sensor bev perception? In 2023 IEEE International Conference on Robotics and Automation (ICRA), pages 2759–2765

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.406485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d0fa28a8-9dbf-42b0-bab2-4a25f55ff331 · outbound

This paper cites Long short-term memory.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Long short-term memory

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T06:02:58.198857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebdb0afa-fa2d-4bdd-ac9b-c83b6bbc2ec1 · outbound

This paper cites HOPE: Hierarchical Spatial-temporal Network for Occupancy Flow Prediction.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting HOPE: Hierarchical Spatial-temporal Network for Occupancy Flow Prediction

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-07T06:02:58.296241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 309e34d2-62a9-41dd-a186-13d42f9b17e0 · outbound

This paper cites VectorFlow: Combining Images and Vectors for Traffic Occupancy and Flow Prediction.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting VectorFlow: Combining Images and Vectors for Traffic Occupancy and Flow Prediction

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-07T06:02:58.280409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 512158d7-f693-452f-a7e6-3605001cdd10 · outbound

This paper cites Hybrid-prediction integrated planning for autonomous driving.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Hybrid-prediction integrated planning for autonomous driving

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.387718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a858b36e-0422-4777-b423-a45762f75853 · outbound

This paper cites Multi-modal hierarchical transformer for occupancy flow field prediction in autonomous driving.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Multi-modal hierarchical transformer for occupancy flow field prediction in autonomous driving

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.377944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c7fb5b5a-0a22-414d-a043-8df189f47ae2 · outbound

This paper cites Occupancy flow fields for motion forecasting in autonomous driving.IEEE Robotics and Automation Letters, 7(2):5639– 5646, 2022.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Occupancy flow fields for motion forecasting in autonomous driving.IEEE Robotics and Automation Letters, 7(2):5639– 5646, 2022

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.368254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b50a48dc-dc25-4212-a0cc-99e603da9a54 · outbound

This paper cites Ofmpnet: Deep end-to-end model for occupancy and flow prediction in urban environment.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Ofmpnet: Deep end-to-end model for occupancy and flow prediction in urban environment

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.356870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 07a83390-aba6-4048-b8a1-ca3a205f7ffe · outbound

This paper cites Con- volutional lstm network: A machine learning approach for precipitation nowcasting.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Con- volutional lstm network: A machine learning approach for precipitation nowcasting

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.347129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2df0c94f-a118-4230-b059-e03560053406 · outbound

This paper cites Unsupervised learning of video representa- tions using lstms.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Unsupervised learning of video representa- tions using lstms

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.337222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b675a021-ee84-4bc6-90f9-461c8ad245df · outbound

This paper cites Sequence to sequence learning with neural networks.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Sequence to sequence learning with neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:02:58.325981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 894d4df8-fe23-4dec-941b-d99e4976bbdf · outbound

This paper cites Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting.

CCLSTM: Coupled Convolutional Long-Short Term Memory Network for Occupancy Flow Forecasting Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T06:02:58.233008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.