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Paper Citation Record · LEDGER

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2507.04634.

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

pith.paper-citation-record.v1
2507.04634 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:47:52.594457Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

32 of 32 outbound references displayed

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  • unresolved2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 094f44c5-14c9-4fc5-b79a-e78d3e7dd44b · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Scene Transformer: A unified architecture for predicting multiple agent trajectories

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a613c3ad-4cd5-45e5-830e-82187e317b02 · outbound

This paper cites Pedestrian trajectory predic- tion combining probabilistic reasoning and sequence learning,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Pedestrian trajectory predic- tion combining probabilistic reasoning and sequence learning,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 8b5e98ed-aef8-4ce5-9e36-889d06eb8ac4 · outbound

This paper cites A survey on trajectory-prediction methods for autonomous driving,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction A survey on trajectory-prediction methods for autonomous driving,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 90d59e82-e006-4c8f-92fc-3c1bd2f38695 · outbound

This paper cites Macformer: Map-agent coupled transformer for real-time and robust trajectory prediction,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Macformer: Map-agent coupled transformer for real-time and robust trajectory prediction,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ec67efc4-0498-4625-8613-8ac691073566 · outbound

This paper cites Where will the oncoming vehicle be the next second?.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Where will the oncoming vehicle be the next second?

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 32c11bae-ac72-46ec-8dfa-68e13b0501e4 · outbound

This paper cites Recognition of dangerous situations within a cooperative group of vehicles,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Recognition of dangerous situations within a cooperative group of vehicles,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3ff8ceb2-0c48-4413-ac0f-739fc79719f2 · outbound

This paper cites Model-based threat assessment for avoiding arbitrary vehicle collisions,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Model-based threat assessment for avoiding arbitrary vehicle collisions,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:50.265340Z digest=sha256:9bc8d3fe95af960f823e1f8238e0a857fec91f4bf4ba2e14ed77ecd455b13d6d

Observation 92fd0fdc-a1e9-4fa8-9cd6-4d57cdb50453 · outbound

This paper cites An integrated approach to maneuver-based trajectory prediction and criticality assessment in arbitrary road environments,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction An integrated approach to maneuver-based trajectory prediction and criticality assessment in arbitrary road environments,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:50.408772Z digest=sha256:9dd3d4f894973e5b26e83573b9cdeeb95008681bdb5e8ebd56e713ce475cedc8

Observation aa832541-3444-4fad-b460-8519ebe0f373 · outbound

This paper cites A game-theoretic approach to replanning-aware interactive scene prediction and planning,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction A game-theoretic approach to replanning-aware interactive scene prediction and planning,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:50.495116Z digest=sha256:b5723280ce198a08856e7b2171a4e9790b91c498367e0d0e57a406c052c31958

Observation 65cb2b7f-d6ef-4ea3-aa6f-7b5336072f79 · outbound

This paper cites Probabilistic intention prediction and trajectory generation based on dynamic bayesian net- works,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Probabilistic intention prediction and trajectory generation based on dynamic bayesian net- works,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:50.636439Z digest=sha256:5b500545a033ec5c17b5d5fd9653f9097e1123a80dc867e486b4b3e418346251

Observation 181c2b4e-b38b-4cf6-8f2d-ff4358585146 · outbound

This paper cites A dynamic bayesian network for vehicle maneuver prediction in highway driving scenarios: Framework and verification,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction A dynamic bayesian network for vehicle maneuver prediction in highway driving scenarios: Framework and verification,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation af44aee6-0a30-4771-b8c0-5c7899776c6a · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Social lstm: Human trajectory prediction in crowded spaces,

Reference 12

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raw_fallback, observed 2026-08-06T19:47:53.038613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:50.810818Z digest=sha256:aa2978183a5f277a2c930d53f7a5ad02b244c42cabff6426a5c2fd1cce022b52

Observation 03cd6cbd-7991-44c5-a05d-a0879e4de80e · outbound

This paper cites Traphic: Tra- jectory prediction in dense and heterogeneous traffic using weighted interactions,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Traphic: Tra- jectory prediction in dense and heterogeneous traffic using weighted interactions,

Reference 13

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raw_fallback, observed 2026-08-06T19:47:53.021785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:50.887381Z digest=sha256:72bd30167db3116f9e64038fc7952cc6b62d658431bc5c5743501a8fee2c6c2d

Observation 01596188-8228-4160-8ac2-10f67551d5b3 · outbound

This paper cites Trafficpredict: Trajectory prediction for heterogeneous traffic-agents,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Trafficpredict: Trajectory prediction for heterogeneous traffic-agents,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T19:47:53.004694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:50.948061Z digest=sha256:3a3898df33766eb7ccaa6fb3e0b02c5ca1f67f2d7358bbe7788fc9263b9441c6

Observation 44a758f1-dcef-4732-b1b8-6899e4072c31 · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Vectornet: Encoding hd maps and agent dynamics from vectorized representation,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.077046Z digest=sha256:5594a8a8e6c54ca21832605af4d9a622cb03adbc434382c737dfe023a287e81b

Observation 9af8891f-20d6-43f1-bd3f-83011e94334e · outbound

This paper cites Leveraging future relationship reasoning for vehicle trajectory prediction,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Leveraging future relationship reasoning for vehicle trajectory prediction,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3a2e06f8-d9b4-40ef-8047-d7e91a66e9a0 · outbound

This paper cites Groupnet: Multiscale hypergraph neural networks for trajectory prediction with relational reasoning,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Groupnet: Multiscale hypergraph neural networks for trajectory prediction with relational reasoning,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 55c183d6-3415-4892-8607-ffa959e1f73d · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Hdgt: Heterogeneous driving graph transformer for multi-agent trajectory prediction via scene encoding,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.354313Z digest=sha256:eac455bd9b0ca7cf7328ed8555428f04e9b2c7b2477a57f22eabb717045acfd7

Observation f7a2c6db-5ecb-4f14-ad47-b1dcd0e15ba6 · outbound

This paper cites Gsan: Graph self-attention network for learning spatial–temporal interaction representation in autonomous driving,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Gsan: Graph self-attention network for learning spatial–temporal interaction representation in autonomous driving,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.455150Z digest=sha256:9a67db6a3a456a5f3e26bcf7ac7e24e63d74813c10ba11024618a6fa9dbd66be

Observation 5edf50b2-cd7f-4dc5-95e5-317fa96c0cc2 · outbound

This paper cites A novel transformer-based model for motion forecasting in connected automated vehicles,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction A novel transformer-based model for motion forecasting in connected automated vehicles,

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.528152Z digest=sha256:d6b4eff9a893889df45f3421e1e5b8795baa1b1c94cb06ec6d6762899e29e462

Observation e76503fd-784d-4b11-914d-a6d4f72f8d63 · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Hivt: Hierarchical vector transformer for multi-agent motion prediction,

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-06T19:47:52.896555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.651443Z digest=sha256:4a2687b17b22fd0136fe065c48ce6986159c33791c3193f16a52fe45f8d0aee6

Observation 3c9c97aa-a20a-4c22-befe-f6771f484cde · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Wayformer: Motion forecasting via simple & efficient attention networks,

Reference 22

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raw_fallback, observed 2026-08-06T19:47:52.881021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.689355Z digest=sha256:3711151985e126e789b015b4de5a5cb59a62b0e00acc3beef2482c30cf162c86

Observation 9ba44cff-7941-4e04-9217-9df25312ac1e · outbound

This paper cites Hierarchical vector transformer vehicle trajectories prediction with diffusion convolutional neural networks,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Hierarchical vector transformer vehicle trajectories prediction with diffusion convolutional neural networks,

Reference 23

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raw_fallback, observed 2026-08-06T19:47:52.865544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.810653Z digest=sha256:905d5a38389ebfa87422430bfcf4c1cb5a808df2d06c2688590e559da13dbe6d

Observation 3b1401e8-11ff-4005-9cf0-ef51dcf6bdd3 · outbound

This paper cites A lightweight lane-guided vector transformer for multi-agent trajectory prediction in autonomous driving,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction A lightweight lane-guided vector transformer for multi-agent trajectory prediction in autonomous driving,

Reference 24

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raw_fallback, observed 2026-08-06T19:47:52.849211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.891592Z digest=sha256:0e2f5b882d28877200a2f450fb37894750cbabe80de3376e4eea8b73b59b05e5

Observation d063b7d5-94e2-4715-8534-69313b600c9c · outbound

This paper cites Laformer: Trajectory prediction for autonomous driving with lane-aware scene constraints,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Laformer: Trajectory prediction for autonomous driving with lane-aware scene constraints,

Reference 25

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raw_fallback, observed 2026-08-06T19:47:52.832834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:51.972614Z digest=sha256:4960eb3367caa817aa7a886d87d4522bdf53d175be6c7a9e8cd59bdf9ec3ab8b

Observation a8c39b5e-e237-4616-b0fe-8311b86ffa53 · outbound

This paper cites Prophnet: Efficient agent-centric motion forecasting with anchor-informed proposals,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Prophnet: Efficient agent-centric motion forecasting with anchor-informed proposals,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:52.009431Z digest=sha256:46222bf1c79ca900be62f2984ade924ef5a540e9c6d3fc454456ad8dfd9b0a23

Observation b1709cd6-35c4-41a6-ab38-1b007f1e5313 · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Motion transformer with global intention localization and local movement refinement,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:52.796688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:52.130092Z digest=sha256:8a0340f8f7d8a75688cbc581e3b7c45b75422cf165786bb1cef26c28a698b198

Observation 401bfea0-d97e-4895-8ba7-bcea2cf63fe6 · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Multipath++: Efficient information fusion and trajectory aggregation for behavior prediction,

Reference 28

Resolution
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raw_fallback, observed 2026-08-06T19:47:52.779541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:52.231392Z digest=sha256:c3a3200d2939401409d98ddcb3734eca7e59be1121d45af3da5cc3a378ad84c2

Observation bc79b8cc-b028-4bec-a9e0-0d439858d191 · outbound

This paper cites R-pred: Two-stage motion prediction via tube-query attention-based trajectory refinement,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction R-pred: Two-stage motion prediction via tube-query attention-based trajectory refinement,

Reference 29

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raw_fallback, observed 2026-08-06T19:47:52.763598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:52.306181Z digest=sha256:b65e3b9e906597db7ff0b0526f25c3eedf023033d451d75684c6807d247bcb50

Observation ac508b4b-b071-4183-b94e-48b57bab87d6 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:47:52.414925Z digest=sha256:91b3735b4d2312d1a7fbe2808e7411dfab04874065e1085ee5f5c10842ead3c4

Observation df352f3a-e3c4-4dac-b088-0baebae4b005 · outbound

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

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Densetnt: End-to-end trajectory pre- diction from dense goal sets,

Reference 31

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raw_fallback, observed 2026-08-06T19:47:52.748543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:52.487529Z digest=sha256:a99a9a4bf08d46dac15b078963e6aa5e29af8e0deaf7ce88aa56f9a8947bc248

Observation 1f9a3ffb-ea93-4e4b-8f9d-f6a3db168d1e · outbound

This paper cites Ltp: Lane-based trajectory prediction for autonomous driving,.

LTMSformer: A Local Trend-Aware Attention and Motion State Encoding Transformer for Multi-Agent Trajectory Prediction Ltp: Lane-based trajectory prediction for autonomous driving,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:52.733179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:47:52.594457Z digest=sha256:7ddfe3162f7a800362f1878eda63e7497fa036321f23a519ceeb7e24a1b79fd8

Pith citing papers

No inbound Pith citation observations are available.