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Paper Citation Record · LEDGER

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction

As of 9 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2606.00857.

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

pith.paper-citation-record.v1
2606.00857 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T18:22:05.384127Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

48 of 48 outbound references displayed

  • verified exact7
  • verified fuzzy0
  • unresolved40
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2bac6ed5-45cd-48ea-93a7-f96712379f75 · outbound

This paper cites Machine learning for autonomous vehicle’s trajectory prediction: A comprehensive survey, challenges, and future research directions,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Machine learning for autonomous vehicle’s trajectory prediction: A comprehensive survey, challenges, and future research directions,

Reference 1

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Observation 601291f5-a237-4c5f-b12a-8a3a183e405b · outbound

This paper cites Post-interactive Multimodal Trajectory Prediction for Autonomous Driving.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Post-interactive Multimodal Trajectory Prediction for Autonomous Driving

Reference 2

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arxiv_id, observed 2026-06-28T20:42:37.828126Z

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Observation debfcf4d-fd28-4674-9b78-b589b19f9ca2 · outbound

This paper cites GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving

Reference 3

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Observation 1b2be663-f82b-4c4b-9f73-024dd1585156 · outbound

This paper cites Ai-tp: Attention- based interaction-aware trajectory prediction for autonomous driving,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Ai-tp: Attention- based interaction-aware trajectory prediction for autonomous driving,

Reference 4

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Observation 51a93b74-237d-4bc4-9794-f8d0c7676431 · outbound

This paper cites Ise-gt: In- teraction strength-enhanced graph transformer for explainable multi- agent trajectory prediction,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Ise-gt: In- teraction strength-enhanced graph transformer for explainable multi- agent trajectory prediction,

Reference 5

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Observation 7dfdd0ff-b547-4faa-b3ce-082bb2206186 · outbound

This paper cites Context-aware trajectory prediction for autonomous driving in heterogeneous environments,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Context-aware trajectory prediction for autonomous driving in heterogeneous environments,

Reference 6

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Observation 688c62cc-440c-4bf0-a780-3ed4015ab739 · outbound

This paper cites Bat: Behavior-aware human-like trajectory prediction for autonomous driv- ing,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Bat: Behavior-aware human-like trajectory prediction for autonomous driv- ing,

Reference 7

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Observation 8ab00c50-1312-4aca-b609-97b9e264a49e · outbound

This paper cites Dual transformer based prediction for lane change intentions and trajectories in mixed traffic environment,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Dual transformer based prediction for lane change intentions and trajectories in mixed traffic environment,

Reference 8

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Observation 00874852-990f-4669-af32-041455756c4e · outbound

This paper cites Interaction-aware cut-in trajectory prediction and risk assessment in mixed traffic,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Interaction-aware cut-in trajectory prediction and risk assessment in mixed traffic,

Reference 9

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Observation ce2aa6bf-0460-4c94-bb84-4634fdf1897d · outbound

This paper cites Incorpo- rating safety field theory into interactive trajectory prediction between vru and vehicle: An integrated spatial–temporal and risk-aware model,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Incorpo- rating safety field theory into interactive trajectory prediction between vru and vehicle: An integrated spatial–temporal and risk-aware model,

Reference 10

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Observation 135c2048-5c45-45a2-971f-a992c74983bd · outbound

This paper cites Risk- aware vehicle trajectory prediction under safety-critical scenarios,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Risk- aware vehicle trajectory prediction under safety-critical scenarios,

Reference 11

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Observation c4890a20-c54a-4324-9fac-c36c0659ad48 · outbound

This paper cites Probabilistic vehicle trajectory prediction over occupancy grid map via recurrent neural network,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Probabilistic vehicle trajectory prediction over occupancy grid map via recurrent neural network,

Reference 12

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Observation 7c6476e9-804f-4b6a-a3bc-5f3214e60666 · outbound

This paper cites Vehicle trajectory prediction using lstms with spatial–temporal attention mechanisms,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Vehicle trajectory prediction using lstms with spatial–temporal attention mechanisms,

Reference 13

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Observation ec6f88a8-630d-4fa1-b28a-a5070bf7d7e6 · outbound

This paper cites Bart ´e: Composite b ´ezier curves for racing trajectory estimation,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Bart ´e: Composite b ´ezier curves for racing trajectory estimation,

Reference 14

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Observation ebe490b3-7df8-4b03-aceb-b7769e11e092 · outbound

This paper cites Learning lane graph representations for motion forecasting,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Learning lane graph representations for motion forecasting,

Reference 15

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Observation 8c07566f-6991-4a2c-8329-f07f3ecd9ad1 · outbound

This paper cites Evolvegraph: Multi-agent trajectory prediction with dynamic relational reasoning,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Evolvegraph: Multi-agent trajectory prediction with dynamic relational reasoning,

Reference 16

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Observation b250acf0-f07e-4f99-aa8b-4fdcc6f831f6 · outbound

This paper cites Ms-tip: imputation aware pedestrian trajectory prediction,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Ms-tip: imputation aware pedestrian trajectory prediction,

Reference 17

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:ef4815918e3960952131f9ea46bb331612f39b2b9bfd4fbc55a3670b04166ade

Observation 7f253027-4e09-4c59-901f-49af223ebd77 · outbound

This paper cites Motion transformer with global intention localization and local movement refinement,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Motion transformer with global intention localization and local movement refinement,

Reference 18

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Observation 24dbe64e-81a0-4ab4-adae-2b95d34db918 · outbound

This paper cites Fif: future interaction forecasted for multi-agent trajectory prediction,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Fif: future interaction forecasted for multi-agent trajectory prediction,

Reference 19

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Observation c2d4a977-9bcf-43c2-844d-1b41c780ec2e · outbound

This paper cites Social gan: Socially acceptable trajectories with generative adversarial networks,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Social gan: Socially acceptable trajectories with generative adversarial networks,

Reference 20

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Observation 29931c68-92ae-4bce-9621-12693dbc6cd0 · outbound

This paper cites A novel generation-adversarial-network-based vehicle trajectory prediction method for intelligent vehicular networks,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction A novel generation-adversarial-network-based vehicle trajectory prediction method for intelligent vehicular networks,

Reference 21

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Observation be2bfe89-1876-4b98-a0f9-2c90e46b4d0a · outbound

This paper cites Diffusion-Based Environment-Aware Trajectory Prediction.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Diffusion-Based Environment-Aware Trajectory Prediction

Reference 22

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Observation 1b05a27f-4300-4ed5-a7a7-293aa243e8e5 · outbound

This paper cites Intp-dm: Intention- aware multimodal vehicle trajectory prediction using diffusion model,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Intp-dm: Intention- aware multimodal vehicle trajectory prediction using diffusion model,

Reference 23

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:0c42d0afb665c638a316142e0bb3629cd685dd9d8c8b87baed06e96d6d2cc6e9

Observation fad58e20-f6ed-403c-a25a-bd0d00b1aa5e · outbound

This paper cites Vehicle trajec- tory prediction based on intention-aware non-autoregressive transformer with multi-attention learning for internet of vehicles,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Vehicle trajec- tory prediction based on intention-aware non-autoregressive transformer with multi-attention learning for internet of vehicles,

Reference 24

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Observation 0c12c1cc-903d-4557-ba21-37722a8870e8 · outbound

This paper cites Tnt: Target-driven trajectory prediction,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Tnt: Target-driven trajectory prediction,

Reference 25

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:c4cc68c54cec3768d9994aef6325a36c7125b507dec63807f7938d9e0a01c6d9

Observation 5255ce3f-24f3-48f9-89bf-444fd51f5888 · outbound

This paper cites Goal-guided and interaction- aware state refinement graph attention network for multi-agent trajectory prediction,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Goal-guided and interaction- aware state refinement graph attention network for multi-agent trajectory prediction,

Reference 26

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Observation aeb85a87-3b42-4cea-b776-afa0d648a1e7 · outbound

This paper cites Densetnt: End-to-end trajectory prediction from dense goal sets,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Densetnt: End-to-end trajectory prediction from dense goal sets,

Reference 27

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Observation 54da86eb-c343-4cfe-9605-55f388596e4d · outbound

This paper cites SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics

Reference 28

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:ec2f71d2ba4740e1020a9526d3091ef29d6760f99a7c3b26a7cbec936b1c8caa

Observation df3e74e4-ad5c-49ba-8d13-ddeb1e7f044d · outbound

This paper cites Interactive trajectory prediction using a driving risk map-integrated deep learning method for surrounding vehicles on highways,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Interactive trajectory prediction using a driving risk map-integrated deep learning method for surrounding vehicles on highways,

Reference 29

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:09c3cccc5cfca3190245088b952fca7fb595fd280e60825f880e35f94f030760

Observation e3bf6775-6e7a-45d2-b0ef-922ba9ea5213 · outbound

This paper cites Sa-tp 2: A safety-aware trajectory prediction and planning model for autonomous driving,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Sa-tp 2: A safety-aware trajectory prediction and planning model for autonomous driving,

Reference 30

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Observation ef11c2d2-8bd1-4bea-9719-36098f7b5a9b · outbound

This paper cites Heterogeneous trajectory forecasting via risk and scene graph learning,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Heterogeneous trajectory forecasting via risk and scene graph learning,

Reference 31

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Observation f90ed3f8-329f-4b38-bcb1-a98246f1953c · outbound

This paper cites Risk-aware stochastic vehicle trajectory prediction with spatial-temporal interaction modelling,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Risk-aware stochastic vehicle trajectory prediction with spatial-temporal interaction modelling,

Reference 32

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Observation 1e398cf3-6d95-48b5-8fed-53f17e2000eb · outbound

This paper cites Intention-based and Risk-Aware Trajectory Prediction for Autonomous Driving in Complex Traffic Scenarios.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Intention-based and Risk-Aware Trajectory Prediction for Autonomous Driving in Complex Traffic Scenarios

Reference 33

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:75586fd9b35fd8fa6e6e0fdf2e44d4b03b8618bfa8021587541be1d1a041be9c

Observation f04d7f6c-6b9b-4912-9da8-b68df18105a6 · outbound

This paper cites Ttc-slstm: Human trajectory prediction using time-to-collision interac- tion energy,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Ttc-slstm: Human trajectory prediction using time-to-collision interac- tion energy,

Reference 34

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Observation a1977b12-537b-4fb0-af78-70c6966e5f68 · outbound

This paper cites STRAP: Spatial-Temporal Risk-Attentive Vehicle Trajectory Prediction for Autonomous Driving.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction STRAP: Spatial-Temporal Risk-Attentive Vehicle Trajectory Prediction for Autonomous Driving

Reference 35

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:427bff14ffb1be2464f286c74c1ec010bb7ddd7130c3b23fa6cf103090c2341d

Observation c1e373ef-207e-4f28-acef-772642a8e8ad · outbound

This paper cites Risk-aware trajectory prediction by incorporating spatio-temporal traffic interaction analysis,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Risk-aware trajectory prediction by incorporating spatio-temporal traffic interaction analysis,

Reference 36

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Observation adce51dc-923c-4711-9241-a684ff418c6c · outbound

This paper cites Composite Safety Potential Field for Highway Driving Risk Assessment.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Composite Safety Potential Field for Highway Driving Risk Assessment

Reference 37

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verified exact
arxiv_id, observed 2026-06-28T20:42:37.830783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:f9fe2d16862c017a8c69f07ba817f66c6c1f3de553e58385c8a596c8d8c7d876

Observation 2d0b0464-4774-4c37-948e-60a438b4de88 · outbound

This paper cites Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction

Reference 38

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verified exact
arxiv_id, observed 2026-06-28T20:42:37.820848Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:da4683fe3ce1b86a64f966de10b439dfff3e51f4760cfd185d4e8ef08d8be447

Observation 5ed03db9-4ee1-4ae2-b7da-428c2092be62 · outbound

This paper cites The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,

Reference 39

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:74b384457eb040e17b9cf0d9d12292280ed4974b5f34b1dd3e4fc9453e54c240

Observation 1973216d-4d63-4705-98a9-6ce344e85c2a · outbound

This paper cites Bird’s eye view trajectory reconstruction of naturalistic crashes and near-crashes in the shrp2 nds,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Bird’s eye view trajectory reconstruction of naturalistic crashes and near-crashes in the shrp2 nds,

Reference 40

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:1ac59daa9362c32949919f1c9da9f768b4e740c3ee6bed49ce50db0e4cf5a8fc

Observation b580aeb9-b20a-47d0-bff2-95d793511d86 · outbound

This paper cites Description of the shrp 2 naturalistic database and the crash, near-crash, and baseline data sets,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Description of the shrp 2 naturalistic database and the crash, near-crash, and baseline data sets,

Reference 41

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:1c68974967e03bd97a3885ba4329ba2d9fa314197e440ec467dda7ead0a82f97

Observation 965f6b46-63db-4337-9c4a-0452ba9e626d · outbound

This paper cites Social lstm: Human trajectory prediction in crowded spaces,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Social lstm: Human trajectory prediction in crowded spaces,

Reference 42

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unresolved
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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:bc29e41b0c4ad1b3f5805a89e91018f87642eb149a240a51c8ef0b5bd726f300

Observation 9de67278-1c3d-489e-a6a8-4b9c2fbb5964 · outbound

This paper cites Convolutional social pooling for vehicle tra- jectory prediction,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Convolutional social pooling for vehicle tra- jectory prediction,

Reference 43

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:a82d0ed867c02f4d0332bcc40459371141387e5730f59ebbe5952b5668896942

Observation a6adef54-26e5-4432-ad1b-46ddd6d51b42 · outbound

This paper cites Wsip: Wave superposition inspired pooling for dynamic interactions-aware trajectory prediction,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Wsip: Wave superposition inspired pooling for dynamic interactions-aware trajectory prediction,

Reference 44

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:8cc4500e236de1e8f609053946f29580236a02367d89402cbd2de692aa2e21be

Observation 69626c22-319e-4278-9823-51ad5b1f0f3d · outbound

This paper cites Goal-based neural physics vehicle trajectory prediction model,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Goal-based neural physics vehicle trajectory prediction model,

Reference 45

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:e1ec144e35c6c00354217c0489ae1bc4f176518801f8f13c4aaece71671176bd

Observation 21cbe6d7-c45a-43e0-8cb7-024724258e3b · outbound

This paper cites Pip: Planning-informed trajectory prediction for autonomous driving,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Pip: Planning-informed trajectory prediction for autonomous driving,

Reference 46

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:65044d3ffc1d5ec21bff5fa82aebb99bdfb7476033ea71a01e8b2488fa2e0ccc

Observation 04aaa86c-84f4-4d31-b588-5b5b3dc8ad8b · outbound

This paper cites Intention- aware vehicle trajectory prediction based on spatial-temporal dynamic attention network for internet of vehicles,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction Intention- aware vehicle trajectory prediction based on spatial-temporal dynamic attention network for internet of vehicles,

Reference 47

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:652548d27ae4d7e4d7c38dddb0fbc9321583327f7e617cc67949038d8a281783

Observation 9b51caf0-8d0a-4489-8e0e-203d03044884 · outbound

This paper cites A cognitive-based trajectory prediction approach for autonomous driving,.

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction A cognitive-based trajectory prediction approach for autonomous driving,

Reference 48

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source=pdf_text observed=2026-06-28T18:22:05.384127Z digest=sha256:f1e25bfadd9661ef91e18d0088a6045e699d75334d1cb6d505b352af56b02aa9

Pith citing papers

No inbound Pith citation observations are available.