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Paper Citation Record · LEDGER

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations

As of 18 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2509.06665.

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

pith.paper-citation-record.v1
2509.06665 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:23:13.413358Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

28 of 28 outbound references displayed

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  • verified fuzzy12
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External citation measurements

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Outbound references

Observation c4b3f8bb-d2a6-4b35-b648-7dc03a3c89d4 · outbound

This paper cites Interworking of dsrc and cellular network technologies for v2x communications: A survey,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Interworking of dsrc and cellular network technologies for v2x communications: A survey,

Reference 1

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9125da6e-b399-44d1-b8c6-ec2959342f5a · outbound

This paper cites Qmr: Q-learning based multi-objective optimization routing protocol for flying ad hoc networks,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Qmr: Q-learning based multi-objective optimization routing protocol for flying ad hoc networks,

Reference 2

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5e76ad24-8733-40b6-932d-4357dd0c8466 · outbound

This paper cites Dealing with changes: Resilient routing via graph neural networks and multi-agent deep reinforcement learning,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Dealing with changes: Resilient routing via graph neural networks and multi-agent deep reinforcement learning,

Reference 3

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d07b1367-5ce7-48be-aa40-f50079d68c82 · outbound

This paper cites Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Deep reinforcement learning meets graph neural networks: Exploring a routing optimization use case,

Reference 4

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Observation b90204f9-62d0-4fc9-95c8-91034a2f40ff · outbound

This paper cites Gddr: Gnn-based data-driven routing,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Gddr: Gnn-based data-driven routing,

Reference 5

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2bc365e8-7ff2-4772-be09-f1349d6e14c8 · outbound

This paper cites Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing

Reference 6

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Observation 9458e4ab-8e76-4e46-b155-4ac254d2648c · outbound

This paper cites Graph neural networks for wireless networks: Graph representation, architecture and evaluation,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Graph neural networks for wireless networks: Graph representation, architecture and evaluation,

Reference 7

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 516f2278-99cd-481e-8cc0-b42541d522c3 · outbound

This paper cites Attention is all you need,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Attention is all you need,

Reference 8

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Observation 5b5a6f67-6a92-4c78-b857-6b8a059c81f7 · outbound

This paper cites Gtat: empowering graph neural networks with cross attention,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Gtat: empowering graph neural networks with cross attention,

Reference 9

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Observation 45debc11-0e36-4ce0-8f97-3068a69090fb · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral filtering,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Convolutional neural networks on graphs with fast localized spectral filtering,

Reference 10

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Observation 4e6bdfc8-7646-4623-94b2-29856fcb55d0 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Semi-Supervised Classification with Graph Convolutional Networks

Reference 11

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Observation d347e829-f325-41a7-9262-f5e099f3b664 · outbound

This paper cites Representation learning on graphs with jumping knowledge networks,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Representation learning on graphs with jumping knowledge networks,

Reference 12

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7189730c-1fea-41f5-b645-dd3ba94fa580 · outbound

This paper cites Inductive representation learning on large graphs,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Inductive representation learning on large graphs,

Reference 13

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Observation b92bd11e-7945-4a23-8825-7a38c4ffa673 · outbound

This paper cites Graph Convolutional Reinforcement Learning.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Graph Convolutional Reinforcement Learning

Reference 14

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Observation 63c87343-33f6-4cec-87f5-20003322e0ef · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Playing Atari with Deep Reinforcement Learning

Reference 15

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Observation e47dfc03-de94-467c-8010-7344328c5aa8 · outbound

This paper cites Reinforcement learning: A survey,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Reinforcement learning: A survey,

Reference 16

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Observation 6a6fd5b0-64b7-422b-95e7-cf4f36b14520 · outbound

This paper cites Human-level control through deep reinforcement learning,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Human-level control through deep reinforcement learning,

Reference 17

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Observation e443baf6-dbb7-4daa-83d9-d43c7a15bedf · outbound

This paper cites Approximation by superpositions of a sigmoidal function,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Approximation by superpositions of a sigmoidal function,

Reference 18

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Observation 936a6ef0-2f55-4648-a6ed-d30db40ab547 · outbound

This paper cites Deep reinforcement learning for autonomous driving: A survey,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Deep reinforcement learning for autonomous driving: A survey,

Reference 19

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Observation 3b1a16fb-4ad7-4fb2-8c9d-9bbdc6ad9266 · outbound

This paper cites Intelligent routing based on reinforcement learning for software-defined networking,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Intelligent routing based on reinforcement learning for software-defined networking,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a3b5af04-ef72-47f5-b8e8-70cf8a516e89 · outbound

This paper cites House of graphs 2.0: A database of interesting graphs and more,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations House of graphs 2.0: A database of interesting graphs and more,

Reference 21

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Observation 2a49dedd-039a-4844-9e6e-13f6dceeace5 · outbound

This paper cites Uncovering the missing pattern: Unified framework towards trajectory imputation and prediction,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Uncovering the missing pattern: Unified framework towards trajectory imputation and prediction,

Reference 22

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6aa7bdae-b12c-4fcd-9976-f40b4c159cc5 · outbound

This paper cites Robust long-term vehicle trajectory prediction using link projection and a situation-aware transformer,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Robust long-term vehicle trajectory prediction using link projection and a situation-aware transformer,

Reference 23

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8945021e-3cf7-48bd-a353-133b076a39ad · outbound

This paper cites Dedicated short-range communications (dsrc) standards in the united states,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Dedicated short-range communications (dsrc) standards in the united states,

Reference 24

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 73294575-e259-441d-84b2-39c5ed81f33e · outbound

This paper cites On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

Reference 25

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Observation 21c4bed9-2c49-4d85-bee3-28d171872e98 · outbound

This paper cites Microscopic traffic simulation using sumo,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Microscopic traffic simulation using sumo,

Reference 26

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Observation 4147eea1-83e3-44c2-8e01-107133712a3d · outbound

This paper cites Planet dump retrieved from https://planet.osm.org ,.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Planet dump retrieved from https://planet.osm.org ,

Reference 27

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Observation ff7e66be-d620-41cc-a809-29ec07fda1c4 · outbound

This paper cites Available: https://elib.dlr.de/124092/.

TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations Available: https://elib.dlr.de/124092/

Reference 2018

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Pith citing papers

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