Paper Citation Record · LEDGER

Stochastic trajectory prediction with social graph network

As of 23 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 2 inbound Pith citation observations for arXiv:1907.10233.

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

pith.paper-citation-record.v1
1907.10233 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T17:15:34.791694Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T16:37:01.846968Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-30T21:35:05.249245Z

Reference resolution

30 of 30 outbound references displayed

verified exact2
verified fuzzy28
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dc8c194e-33a4-425c-b35d-f6ed64f98fc0 · outbound

This paper cites So- cial lstm: Human trajectory prediction in crowded spaces.

Stochastic trajectory prediction with social graph network So- cial lstm: Human trajectory prediction in crowded spaces

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.008615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dc438e84-40fd-4e09-9a66-4af20b1940b5 · outbound

This paper cites Campbell, and Sergey Levine.

Stochastic trajectory prediction with social graph network Campbell, and Sergey Levine

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.022098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 34611804-30fa-466e-9f04-3f9be3ee87ed · outbound

This paper cites An Evaluation of Trajectory Prediction Approaches and Notes on the TrajNet Benchmark.

Stochastic trajectory prediction with social graph network An Evaluation of Trajectory Prediction Approaches and Notes on the TrajNet Benchmark

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-24T17:16:17.534480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e4f1383d-f600-4fdb-92de-1560a3badf13 · outbound

This paper cites A recurrent latent variable model for sequential data.

Stochastic trajectory prediction with social graph network A recurrent latent variable model for sequential data

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.991123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 95c4e82d-87d5-4b7e-9444-a09f3c3e84d4 · outbound

This paper cites Stochastic video genera- tion with a learned prior.

Stochastic trajectory prediction with social graph network Stochastic video genera- tion with a learned prior

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.012406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cbcf3abb-be86-421b-9720-3b59d85c234a · outbound

This paper cites Where will they go? predicting ﬁne-grained adversarial multi- agent motion using conditional variational autoencoders.

Stochastic trajectory prediction with social graph network Where will they go? predicting ﬁne-grained adversarial multi- agent motion using conditional variational autoencoders

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.983877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ce126905-d677-40a4-9133-5d9cc4fdc68b · outbound

This paper cites Sequential neural models with stochastic lay- ers.

Stochastic trajectory prediction with social graph network Sequential neural models with stochastic lay- ers

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.987721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 441be648-a8eb-41b0-86fb-ee8b5d3cd1b7 · outbound

This paper cites Z-forcing: Training stochastic recurrent networks.

Stochastic trajectory prediction with social graph network Z-forcing: Training stochastic recurrent networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.042963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8b551e73-d033-4605-84be-df49a20ddc43 · outbound

This paper cites Social gan: Socially acceptable tra- jectories with generative adversarial networks.

Stochastic trajectory prediction with social graph network Social gan: Socially acceptable tra- jectories with generative adversarial networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.994576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8525f672-f769-4440-887d-d76a6d23c36d · outbound

This paper cites Social force model for pedestrian dynamics.

Stochastic trajectory prediction with social graph network Social force model for pedestrian dynamics

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.969855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 32ba1a58-46ad-41da-90d4-6d82566b1605 · outbound

This paper cites Choy, Philip H.

Stochastic trajectory prediction with social graph network Choy, Philip H

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.976693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 32405eb6-b18b-4141-98f5-d5e707fae6e3 · outbound

This paper cites Crowds by example.

Stochastic trajectory prediction with social graph network Crowds by example

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.029712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7015f8ba-520c-4817-b1a4-42aa2830d30a · outbound

This paper cites Diffu- sion convolutional recurrent neural network: Data-driven trafﬁc forecasting.

Stochastic trajectory prediction with social graph network Diffu- sion convolutional recurrent neural network: Data-driven trafﬁc forecasting

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.965965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3315139c-824b-4ba1-b1ec-c2ed0a89768d · outbound

This paper cites Trafﬁcpredict: Trajec- tory prediction for heterogeneous trafﬁc-agents.

Stochastic trajectory prediction with social graph network Trafﬁcpredict: Trajec- tory prediction for heterogeneous trafﬁc-agents

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.980087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 291fbb0a-a736-4ce2-b6fa-cf2d9ff52d9f · outbound

This paper cites Egocentric future localization.

Stochastic trajectory prediction with social graph network Egocentric future localization

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.973146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 04e9338e-aca3-4eef-bb7d-ce36900ea9c1 · outbound

This paper cites V an Gool.

Stochastic trajectory prediction with social graph network V an Gool

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.046123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c262b8d9-b9ea-45c5-9027-91e666461df5 · outbound

This paper cites Wrong turn - no dead end: A stochas- tic pedestrian motion model.

Stochastic trajectory prediction with social graph network Wrong turn - no dead end: A stochas- tic pedestrian motion model

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.049248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 90c609b6-1453-407e-b842-cdfd873ec1a5 · outbound

This paper cites Im- proving data association by joint modeling of pedestrian trajectories and groupings.

Stochastic trajectory prediction with social graph network Im- proving data association by joint modeling of pedestrian trajectories and groupings

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.059224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 040fd5ea-4c28-4d25-8df5-50580c6f1bed · outbound

This paper cites R2p2: A reparameterized pushforward policy for diverse, precise generative path forecasting.

Stochastic trajectory prediction with social graph network R2p2: A reparameterized pushforward policy for diverse, precise generative path forecasting

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.039425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c303bf9e-6217-4c83-a5a4-b55b787f2c60 · outbound

This paper cites SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints.

Stochastic trajectory prediction with social graph network SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-24T17:16:17.540092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3eca89ef-0d58-4f22-9b6c-4a2db435e086 · outbound

This paper cites Learn- ing structured output representation using deep conditional generative models.

Stochastic trajectory prediction with social graph network Learn- ing structured output representation using deep conditional generative models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.001276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1d84d4bc-e25c-4465-b6a3-593f41176555 · outbound

This paper cites Forecast the plausible paths in crowd scenes.

Stochastic trajectory prediction with social graph network Forecast the plausible paths in crowd scenes

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.019119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 539a5929-b09c-46b7-a15a-c397c008f7e1 · outbound

This paper cites Stochastic prediction of multi-agent interactions from partial observations.

Stochastic trajectory prediction with social graph network Stochastic prediction of multi-agent interactions from partial observations

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.004727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0859ef56-af9f-4507-91ee-d8f2cbb2af4f · outbound

This paper cites Graph attention networks.

Stochastic trajectory prediction with social graph network Graph attention networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:17.997746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ecddc280-bca7-4890-9814-63ccd167c3fa · outbound

This paper cites Socia l attention: Modeling attention in human crowds.

Stochastic trajectory prediction with social graph network Socia l attention: Modeling attention in human crowds

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.055786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 95863f2a-11ad-4c10-988c-99adc41a8857 · outbound

This paper cites An uncertain future: Forecasting from static im- ages using variational autoencoders.

Stochastic trajectory prediction with social graph network An uncertain future: Forecasting from static im- ages using variational autoencoders

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.026498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4293318b-c8d9-440f-b336-5b6005b7f91f · outbound

This paper cites Encoding crowd interaction with deep neural network for pedestrian trajectory prediction.

Stochastic trajectory prediction with social graph network Encoding crowd interaction with deep neural network for pedestrian trajectory prediction

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.052786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 003afa02-ca49-4d8a-bd03-787a3e282567 · outbound

This paper cites Future person localization in ﬁrst-person videos.

Stochastic trajectory prediction with social graph network Future person localization in ﬁrst-person videos

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.033002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 195b38bc-f2f1-481c-9e1d-31a61b4e01f7 · outbound

This paper cites Sr-lstm state reﬁnement for pedestrian trajectory prediction.

Stochastic trajectory prediction with social graph network Sr-lstm state reﬁnement for pedestrian trajectory prediction

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.036247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 66098c9c-1676-4998-9efe-e1e49ded1c13 · outbound

This paper cites Understanding human behaviors in crowds by imitating the decision-making process.

Stochastic trajectory prediction with social graph network Understanding human behaviors in crowds by imitating the decision-making process

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T17:16:18.015789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

Observation 2d3240b6-d337-445d-be64-7bd25d02486c · inbound

Exploitation of Hidden Context in Dynamic Movement Forecasting: A Neural Network Journey from Recurrent to Graph Neural Networks and General Purpose Transformers cites this paper.

Exploitation of Hidden Context in Dynamic Movement Forecasting: A Neural Network Journey from Recurrent to Graph Neural Networks and General Purpose Transformers Stochastic trajectory prediction with social graph network

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-06-30T21:35:05.250549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1a584a5c-2840-414c-9d54-64a3646285b5 · inbound

A Dynamic Scene Interaction Reasoning Framework for Scene-level Lane-Change Intention and Trajectory Prediction of Multiple Interacting Vehicles cites this paper.

A Dynamic Scene Interaction Reasoning Framework for Scene-level Lane-Change Intention and Trajectory Prediction of Multiple Interacting Vehicles Stochastic trajectory prediction with social graph network

Reference 149

Resolution: unresolved; no resolver link, observed 2026-07-14T16:37:01.846968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.