Paper Citation Record · LEDGER

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics

As of 9 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2507.12083.

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

pith.paper-citation-record.v1
2507.12083 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:00:00.815339Z

measured 49 of 49 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:27:07.366135Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T06:16:17.936174Z

Reference resolution

48 of 48 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f830a9e6-b09b-4e55-864b-37dfe8e58ba7 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics nuscenes: A multimodal dataset for autonomous driving

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:06.940326Z

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

Observation 541d6884-8ddf-4aa6-b933-e99431e3a572 · outbound

This paper cites End-to- end object detection with transformers.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics End-to- end object detection with transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:06.799642Z

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Observation 9e635c8f-2ac5-4687-8221-b84e63ad6944 · outbound

This paper cites MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction

Reference 3

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Observation 649b8f90-9a5f-4ed2-acfb-6e0d78ef3a9c · outbound

This paper cites Argoverse: 3d tracking and forecasting with rich maps.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Argoverse: 3d tracking and forecasting with rich maps

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:06.660100Z

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Observation 8f62ca50-39bd-4c27-a547-f5c3dee8de93 · outbound

This paper cites Multimodal trajectory predictions for autonomous driving using deep convolutional networks.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Multimodal trajectory predictions for autonomous driving using deep convolutional networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:06.510661Z

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 a8a7ad32-c159-415e-b1a7-cad0d9905ba3 · outbound

This paper cites Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T16:59:54.767777Z

Source-reported events for the cited work

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Observation 5577be57-04df-47ef-9377-7d7580e6be58 · outbound

This paper cites Multimodal trajectory prediction conditioned on lane-graph traversals.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Multimodal trajectory prediction conditioned on lane-graph traversals

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:06.341172Z

Source-reported events for the cited work

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Observation 24e623e4-7257-4e3c-8d67-85110357773a · outbound

This paper cites Mac- former: Map-agent coupled transformer for real-time and ro- bust trajectory prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Mac- former: Map-agent coupled transformer for real-time and ro- bust trajectory prediction

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:06.180289Z

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

Observation 250a1930-c351-4393-90a7-7843fe75acff · outbound

This paper cites UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction

Reference 9

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Source-reported events for the cited work

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Observation 8b3b3605-dac5-4776-994d-4ca6adad729c · outbound

This paper cites Deep inverse reinforcement learning for be- havior prediction in autonomous driving: Accurate forecasts of vehicle motion.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Deep inverse reinforcement learning for be- havior prediction in autonomous driving: Accurate forecasts of vehicle motion

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:06.043239Z

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 b81b768d-dce5-462e-9875-48fcede6ae58 · outbound

This paper cites Vectornet: Encoding hd maps and agent dynamics from vectorized rep- resentation.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Vectornet: Encoding hd maps and agent dynamics from vectorized rep- resentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:05.918450Z

Source-reported events for the cited work

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Observation f6d04ac0-5209-4459-b0da-62f115e4c2b1 · outbound

This paper cites THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics THOMAS: Trajectory Heatmap Output with learned Multi-Agent Sampling

Reference 12

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Observation 6eca647d-3464-449f-9c73-2395832d8e52 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 13

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Observation 2b8dddd1-7d19-4adb-811b-09381c669512 · outbound

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

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Densetnt: End-to-end trajectory prediction from dense goal sets

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:05.672560Z

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 5c9c19c7-9fd6-4096-84d0-c8157255a3c4 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 15

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Source-reported events for the cited work

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Observation 60cf1f9a-dc9c-4fa2-a12b-5f8e65e73320 · outbound

This paper cites Con- ditional predictive behavior planning with inverse reinforce- ment learning for human-like autonomous driving.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Con- ditional predictive behavior planning with inverse reinforce- ment learning for human-like autonomous driving

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:05.361479Z

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 2b12c0cf-a5d8-4b84-b497-596ace650d6b · outbound

This paper cites OpenAI o1 System Card.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics OpenAI o1 System Card

Reference 17

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Source-reported events for the cited work

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Observation a895e4a1-f7bb-4305-8b42-68965062ae1b · outbound

This paper cites Learning lane graph representa- tions for motion forecasting.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Learning lane graph representa- tions for motion forecasting

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:05.109500Z

Source-reported events for the cited work

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Observation 657e6c08-c640-42a0-906f-1507522be6f6 · outbound

This paper cites Kemp: Keyframe-based hierarchical end-to-end deep model for long-term trajectory prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Kemp: Keyframe-based hierarchical end-to-end deep model for long-term trajectory prediction

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:04.874703Z

Source-reported events for the cited work

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Observation fe7eaf4c-bc54-4eb7-aaf8-856a29707097 · outbound

This paper cites Deep learning-based vehicle behavior prediction for autonomous driving applica- tions: A review.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Deep learning-based vehicle behavior prediction for autonomous driving applica- tions: A review

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:04.681318Z

Source-reported events for the cited work

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Observation c6f569a6-422f-41ae-9269-a68f9a2e178b · outbound

This paper cites Wayformer: Motion forecasting via simple & efficient attention networks.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Wayformer: Motion forecasting via simple & efficient attention networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:04.461808Z

Source-reported events for the cited work

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Observation 67f50486-9903-4b2b-9cd1-6c1f1f32dcb6 · outbound

This paper cites Algorithms for inverse reinforcement learning.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Algorithms for inverse reinforcement learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:04.170870Z

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Observation ab343bcb-c29f-4bcd-b9fb-d5a4cbd41183 · outbound

This paper cites Scene Transformer: A unified architecture for predicting multiple agent trajectories.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Scene Transformer: A unified architecture for predicting multiple agent trajectories

Reference 23

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Source-reported events for the cited work

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Observation ceb74f58-ffbc-46f1-abd8-29784d08233f · outbound

This paper cites Quadruped robot locomotion in unknown terrain using deep reinforcement learning.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Quadruped robot locomotion in unknown terrain using deep reinforcement learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:03.867149Z

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 2a8d0dd2-9994-4370-829c-c78c52c531eb · outbound

This paper cites An improved dyna-q algorithm for mobile robot path planning 9 in unknown dynamic environment.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics An improved dyna-q algorithm for mobile robot path planning 9 in unknown dynamic environment

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:03.662096Z

Source-reported events for the cited work

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Observation b1087dc3-7802-437c-949c-babc0741cd52 · outbound

This paper cites Sept: Standard-definition map enhanced scene perception and topology reasoning for au- tonomous driving.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Sept: Standard-definition map enhanced scene perception and topology reasoning for au- tonomous driving

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:03.426635Z

Source-reported events for the cited work

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Observation 0540f74f-a3e2-425a-88a9-90be2d14807b · outbound

This paper cites Goirl: Graph-oriented inverse reinforcement learning for multimodal trajectory prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Goirl: Graph-oriented inverse reinforcement learning for multimodal trajectory prediction

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:03.320683Z

Source-reported events for the cited work

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Observation 8309c834-40f0-451f-bc56-d6bc8446f518 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 28

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Source-reported events for the cited work

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Observation c35cbfd4-fd65-4924-85bd-44685c8ff45b · outbound

This paper cites Scene compliant trajectory forecast with agent- centric spatio-temporal grids.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Scene compliant trajectory forecast with agent- centric spatio-temporal grids

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:03.178482Z

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Observation 22732677-fc4a-4098-8861-6beee9e1e005 · outbound

This paper cites U- net: Convolutional networks for biomedical image segmen- tation.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics U- net: Convolutional networks for biomedical image segmen- tation

Reference 30

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Observation 40741c53-66a8-433c-8828-c6c2a614c8ff · outbound

This paper cites Learning agents for uncertain environments.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Learning agents for uncertain environments

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.925492Z

Source-reported events for the cited work

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Observation 079c421e-22f8-4c62-b323-8cabc4f7b978 · outbound

This paper cites Motion transformer with global intention localization and lo- cal movement refinement.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Motion transformer with global intention localization and lo- cal movement refinement

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.813953Z

Source-reported events for the cited work

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Observation 5a27b50a-fb06-428f-9597-dab12ca9411b · outbound

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

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Pip: Planning- informed trajectory prediction for autonomous driving

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.664382Z

Source-reported events for the cited work

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Observation 61e5bc9f-c65f-45d4-8f10-d5e618fc75a5 · outbound

This paper cites Learning to predict vehicle trajectories with model-based planning.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Learning to predict vehicle trajectories with model-based planning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.504280Z

Source-reported events for the cited work

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Observation 5a4ba55c-7637-431e-aa8b-e0c579d69b9f · outbound

This paper cites Reinforcement learning: An introduction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Reinforcement learning: An introduction

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.451749Z

Source-reported events for the cited work

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Observation 9b463942-9320-4736-b4a4-38279fce15dc · outbound

This paper cites Hpnet: Dynamic trajectory fore- casting with historical prediction attention.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Hpnet: Dynamic trajectory fore- casting with historical prediction attention

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.405281Z

Source-reported events for the cited work

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Observation 3fdf61e2-14fb-411e-8114-7c63fe27487b · outbound

This paper cites Multi- path++: Efficient information fusion and trajectory aggrega- tion for behavior prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Multi- path++: Efficient information fusion and trajectory aggrega- tion for behavior prediction

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.384632Z

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 e1ee3617-7982-435f-b162-ca2e11fee85f · outbound

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

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 38

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Source-reported events for the cited work

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Observation 4ef59b33-cf5f-417f-9108-18d1edbbb728 · outbound

This paper cites Efficient sampling-based maximum entropy inverse reinforcement learning with application to autonomous driving.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Efficient sampling-based maximum entropy inverse reinforcement learning with application to autonomous driving

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.377436Z

Source-reported events for the cited work

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Observation c48364c3-403e-48a4-8a05-7959d9fb7f04 · outbound

This paper cites Large-scale cost function learning for path planning using deep inverse reinforcement learning.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Large-scale cost function learning for path planning using deep inverse reinforcement learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.352211Z

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 6872ac3b-5def-4eb9-924b-9e8344e89027 · outbound

This paper cites Goal- lbp: Goal-based local behavior guided trajectory prediction for autonomous driving.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Goal- lbp: Goal-based local behavior guided trajectory prediction for autonomous driving

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:02.161019Z

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 dcc889ed-9d77-4de2-a985-69e5862bd262 · outbound

This paper cites DeMo: Decoupling Motion Forecasting into Directional Intentions and Dynamic States.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics DeMo: Decoupling Motion Forecasting into Directional Intentions and Dynamic States

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T17:00:00.163759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81f069ca-1702-48db-b176-9cd36db8aa78 · outbound

This paper cites Tra- jectory prediction with graph-based dual-scale context fu- sion.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Tra- jectory prediction with graph-based dual-scale context fu- sion

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:01.945674Z

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 d36c8c1b-457e-4ab2-8df4-2bed0efe3735 · outbound

This paper cites Simpl: A simple and efficient multi-agent motion prediction base- line for autonomous driving.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Simpl: A simple and efficient multi-agent motion prediction base- line for autonomous driving

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:01.755075Z

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 b9e6e1a4-7419-4685-89e2-8f027a8a8cf7 · outbound

This paper cites Hivt: Hierarchical vector transformer for multi-agent motion prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Hivt: Hierarchical vector transformer for multi-agent motion prediction

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:01.541281Z

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 bda39123-5a79-4667-84c9-ae591cbbfa33 · outbound

This paper cites Query-centric trajectory prediction.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Query-centric trajectory prediction

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:01.324109Z

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 6db8a691-3257-478a-8857-84aa087b88da · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T17:00:00.721445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 226da59b-b214-4471-ab03-1c1d64b79987 · outbound

This paper cites Maximum entropy inverse reinforcement learning.

Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics Maximum entropy inverse reinforcement learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:00:01.065973Z

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.

Pith citing papers

Observation 9e5c762b-2904-47b5-8663-ee2740047d78 · inbound

A Unified Framework for Trajectory Prediction with Explicit Planning and Reaction Decomposition cites this paper.

A Unified Framework for Trajectory Prediction with Explicit Planning and Reaction Decomposition Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-08T04:27:07.599953Z

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.