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Paper Citation Record · LEDGER

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting

As of 11 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2501.04815.

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

pith.paper-citation-record.v1
2501.04815 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:31:12.182086Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

44 of 44 outbound references displayed

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  • verified fuzzy36
  • unresolved8
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d9de73ed-4961-4fb5-bc73-e97dbebf1506 · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting nuscenes: A multimodal dataset for autonomous driving

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1bfc2c24-c20f-48b2-88ca-c965fb33855f · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 2

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Unavailable: canonical work link unavailable.

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Observation ecc16cf5-bd49-4f25-a123-10ebc3b77d85 · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 5801f6fc-4a4e-4598-9ff1-6c532c5de682 · outbound

This paper cites Pretram: Self-supervised pre-training via connecting trajectory and map.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Pretram: Self-supervised pre-training via connecting trajectory and map

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 40789518-260b-427e-8d2f-7ff97f0d7613 · outbound

This paper cites SEPT: Towards Efficient Scene Representation Learning for Motion Prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting SEPT: Towards Efficient Scene Representation Learning for Motion Prediction

Reference 5

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Source-reported events for the cited work

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Observation c7b36f60-a85a-4302-86a7-5725b417c1cc · outbound

This paper cites Forecast-MAE: Self-supervised pre-training for motion forecasting with masked autoencoders.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Forecast-MAE: Self-supervised pre-training for motion forecasting with masked autoencoders

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ca9906bd-2aa7-49fe-afb8-d9d92d1fa189 · outbound

This paper cites Dyset: A dynamic masked self-distillation approach for robust trajectory prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Dyset: A dynamic masked self-distillation approach for robust trajectory prediction

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 154f2285-3948-446a-8d02-8ca4faac9ee0 · outbound

This paper cites Smartpretrain: Model-agnostic and dataset-agnostic representation learning for motion prediction, 10 2024.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Smartpretrain: Model-agnostic and dataset-agnostic representation learning for motion prediction, 10 2024

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3fb2598d-6492-4e0a-bda6-3f282f9d94f8 · outbound

This paper cites SSL-lanes: Self-supervised learning for motion fore- casting in autonomous driving.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting SSL-lanes: Self-supervised learning for motion fore- casting in autonomous driving

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1ca59c47-aaef-48b0-bc8d-14e892902013 · outbound

This paper cites Social nce: Contrastive learning of socially-aware motion representations.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Social nce: Contrastive learning of socially-aware motion representations

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 587eaf52-1d9c-4770-adf1-3b75ff072c1e · outbound

This paper cites Perceiver: General percep- tion with iterative attention.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Perceiver: General percep- tion with iterative attention

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 6a8ebaad-b9ad-4634-ad63-7b55a51f1eb5 · outbound

This paper cites Perceiver IO: A General Architecture for Structured Inputs & Outputs.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Perceiver IO: A General Architecture for Structured Inputs & Outputs

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9be7401c-d1ab-4415-8150-db9b525ca223 · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Hivt: Hierarchical vector transformer for multi-agent motion prediction

Reference 13

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raw_fallback, observed 2026-08-10T21:31:12.573674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 268b6684-9108-443d-ae43-ef76c0b3ce7f · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Motion transformer with global intention localization and local movement refinement

Reference 14

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raw_fallback, observed 2026-08-10T21:31:12.563405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 1dba0b7f-3ba3-4dca-9907-0822da04d285 · outbound

This paper cites Hpnet: Dynamic trajectory forecasting with historical prediction attention.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Hpnet: Dynamic trajectory forecasting with historical prediction attention

Reference 15

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raw_fallback, observed 2026-08-10T21:31:12.553594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.077007Z digest=sha256:06e064fa6295c9bad05ec3afce0ddf2eb4ed614822dfc2d9d39569fad882aabc

Observation ccfede1d-bd8b-412f-9cd6-56be715c0f54 · outbound

This paper cites Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying

Reference 16

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 5040b8d3-52e8-4b9e-a3bb-2185a7fb704a · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Wayformer: Motion forecasting via simple & efficient attention networks

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 37541a20-695c-402f-9f51-3a032afc93ad · outbound

This paper cites Motionlm: Multi-agent motion forecasting as language modeling.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Motionlm: Multi-agent motion forecasting as language modeling

Reference 18

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation e2660654-585f-4fe3-b34a-778f25e7120a · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Bootstrap your own latent-a new approach to self-supervised learning

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 43ceb9fb-4373-4b1f-a15c-9b4eae03f020 · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction

Reference 20

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Unavailable: canonical work link unavailable.

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Observation b1522105-c620-4f55-abcc-f1e8bdb712e8 · outbound

This paper cites Vision transformers need registers.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Vision transformers need registers

Reference 21

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation ee9ce18c-845f-49cc-8290-620d7d19dfd4 · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Multimodal trajectory prediction conditioned on lane-graph traversals

Reference 22

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raw_fallback, observed 2026-08-10T21:31:12.493170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 3d26d769-930e-41eb-b98c-b9be14cac843 · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Multimodal trajectory predictions for autonomous driving using deep convolutional networks

Reference 23

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raw_fallback, observed 2026-08-10T21:31:12.482160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 98e1e2e0-12ca-45dd-a0ca-9490134dc497 · outbound

This paper cites Latent variable sequential set transformers for joint multi-agent motion prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Latent variable sequential set transformers for joint multi-agent motion prediction

Reference 24

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raw_fallback, observed 2026-08-10T21:31:12.471196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.109543Z digest=sha256:65a59c71a58380095ae6d32b20fcbb9efcbfdc625f70634ff18ad90fff39b1af

Observation 54a29f08-facf-466f-af54-3d243925ccd1 · outbound

This paper cites Scene transformer: A unified architecture for predicting future trajectories of multiple agents.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Scene transformer: A unified architecture for predicting future trajectories of multiple agents

Reference 25

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raw_fallback, observed 2026-08-10T21:31:12.460534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.113177Z digest=sha256:2bc02012a4ec4e652651d056772e0356f385a033b70ee2af800c833fa5dfdbd1

Observation 8615510f-7d08-4fb6-9059-91f64b40d6be · outbound

This paper cites Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction

Reference 26

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raw_fallback, observed 2026-08-10T21:31:12.449583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 33396a6c-f9c2-4b3a-9439-cd64841cc5f6 · outbound

This paper cites Trajectory prediction for autonomous driving based on multi-head attention with joint agent-map representation.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Trajectory prediction for autonomous driving based on multi-head attention with joint agent-map representation

Reference 27

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raw_fallback, observed 2026-08-10T21:31:12.439217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.120265Z digest=sha256:df97cd8814fbb9325b6282b21fb99d68644d4d1a86b364cef3e53a3e68209849

Observation 9c552480-2897-415d-b916-166caaa414c1 · outbound

This paper cites Real-time motion prediction via hetero- geneous polyline transformer with relative pose encoding.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Real-time motion prediction via hetero- geneous polyline transformer with relative pose encoding

Reference 28

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raw_fallback, observed 2026-08-10T21:31:12.428326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.123756Z digest=sha256:5748c3e27f3f51450111d64f6c6b79cfc2b7d1cf1e1abcecd1c2e41d0fa8eff3

Observation 80ae8451-3e59-4419-8de1-cbfca52b9a77 · outbound

This paper cites Vectornet: Encoding hd maps and agent dynamics from vectorized representation.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Vectornet: Encoding hd maps and agent dynamics from vectorized representation

Reference 29

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raw_fallback, observed 2026-08-10T21:31:12.417402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.127902Z digest=sha256:0ae9af9b7395e152e1b77e1a0d634e3c6d0ef8fd6af88da28aa255232fef2651

Observation adab9c4c-ce6d-4989-a77b-6a4bc23e3848 · outbound

This paper cites Lanercnn: Distributed representations for graph-centric motion forecasting.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Lanercnn: Distributed representations for graph-centric motion forecasting

Reference 30

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raw_fallback, observed 2026-08-10T21:31:12.406580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.131447Z digest=sha256:eca63f401d4dc31d15f453c187e475ee5961325b3f028f09c909f7aa2e2de4a5

Observation 52b5aab0-1e5f-4135-a6c3-37c5699ab434 · outbound

This paper cites Adaptive trajectory prediction via transferable gnn.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Adaptive trajectory prediction via transferable gnn

Reference 31

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no resolver link, observed 2026-08-10T21:31:12.134960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:31:12.134960Z digest=sha256:aba09d2234046df33eded32b701f02751602d38c9813b83663238e176104a2b3

Observation b5da0478-f9f7-4209-af08-6b860273fd08 · outbound

This paper cites Multimodal motion prediction with stacked transformers.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Multimodal motion prediction with stacked transformers

Reference 32

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raw_fallback, observed 2026-08-10T21:31:12.389697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.138508Z digest=sha256:abf07a21f49df2034f818a3992d5b74ccedbda6371c2d065063218983fbb33e6

Observation 2be1e56f-438c-46e3-99a4-5e7d352e6458 · outbound

This paper cites Latent variable sequential set transformers for joint multi-agent motion prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Latent variable sequential set transformers for joint multi-agent motion prediction

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.378898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.142047Z digest=sha256:1bbeb4f4a7cf74acb11cd35cd3d777b7f133d25b82630b2bc49308fe6aef3f03

Observation 46d3e926-3728-4cff-8a29-0d8ade5b819b · outbound

This paper cites Query-centric trajectory prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Query-centric trajectory prediction

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.367950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.145648Z digest=sha256:a81d9b3956a9cbcd7a92eadf5896e42d364fdde46a8261ed6b788ba99a3c1120

Observation b8f2df6e-5d75-4670-875e-3aa526f82daf · outbound

This paper cites Learning lane graph representations for motion forecasting.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Learning lane graph representations for motion forecasting

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.356836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.148928Z digest=sha256:46512245a9d41ea59a37de7ee5e9eda719273188a94bb7f57526e5ee1d0b5e2f

Observation 5605bdc3-319f-46f6-a3fc-c183e86610f8 · outbound

This paper cites Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.345879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.152894Z digest=sha256:f6c869da293de70e655d1b21f3796984995a9979fcba581457bf1dc35e9e578e

Observation 8e19599e-990b-40c3-9dc1-cf931eb688c2 · outbound

This paper cites Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.332938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.156422Z digest=sha256:bc0be5f43d54c7783fb3bdbc944351258cb058c0b8e1aef3e4ffa260a43d2672

Observation 6b17bb02-9cf6-459c-9ff3-95e7048d9d16 · outbound

This paper cites Adapt: Efficient multi-agent trajectory prediction with adaptation.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Adapt: Efficient multi-agent trajectory prediction with adaptation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.321658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.159612Z digest=sha256:c2858f6e7dd9af6f11d6700780a8df48a6031b69fca58ff114e4dec80d60f16c

Observation 0e13c359-d81e-47ca-b695-29238d57e6e5 · outbound

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

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Densetnt: End-to-end trajectory prediction from dense goal sets

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.309691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.163580Z digest=sha256:205f020190ee921a379c9575e26dcd50ee75752e5950702d3e6c5d94ee05ca4f

Observation 7175bffd-526f-4d41-b6fe-c11124286b9a · outbound

This paper cites Traj-MAE: Masked Autoencoders for Trajectory Prediction.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Traj-MAE: Masked Autoencoders for Trajectory Prediction

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T21:31:12.166935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:31:12.166935Z digest=sha256:d09d44d2c811992cfd9abe84a1bf2f8cba23bb34304ceac2d161a6f334a5eeee

Observation 03d1ac7e-df02-4d9a-8e08-625e1e82b0d3 · outbound

This paper cites Encoder and decoder, not one less for pre-trained language model sponsored nmt.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Encoder and decoder, not one less for pre-trained language model sponsored nmt

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.297851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.170670Z digest=sha256:a96e0a535bfe93983c82ea1b97421b01bcf41db770d60e4b5eb005265e0adf1c

Observation c52e02e3-d4a9-45cf-aac8-9ddb7d882fbe · outbound

This paper cites Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T21:31:12.174513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:31:12.174513Z digest=sha256:afb068d2c3bfbc453bdddd223324510ad41b041d67f44e60d7ee199c2c5c0b21

Observation 32f3d4e1-bb8c-4015-b012-83c4dfc16603 · outbound

This paper cites Visual prompt tuning.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Visual prompt tuning

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:31:12.285094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T21:31:12.178517Z digest=sha256:616fd5e631ab85f7445e03548f2a1a83b7a7716efa21766f26e088e690364072

Observation b3b5c208-fc20-47f6-80aa-9a26313d4274 · outbound

This paper cites Parameter-Efficient Tuning on Layer Normalization for Pre-trained Language Models.

Towards Generalizable Trajectory Prediction Using Dual-Level Representation Learning And Adaptive Prompting Parameter-Efficient Tuning on Layer Normalization for Pre-trained Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T21:31:12.182086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:31:12.182086Z digest=sha256:dd029203ac698951aea5be247bd68c77fc1643e3b42cfd7b7932a77759d4af11

Pith citing papers

No inbound Pith citation observations are available.