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Paper Citation Record · LEDGER

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues

As of 18 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2507.21161.

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

pith.paper-citation-record.v1
2507.21161 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:07:42.779884Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

19 of 19 outbound references displayed

  • verified exact1
  • verified fuzzy10
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9aa94afd-b4bb-41f9-a00a-b0d21603b093 · outbound

This paper cites an unresolved cited work.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-15T18:07:43.222436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.684756Z digest=sha256:d403d641ffae770d83f78509f34b07b28e71766640c65ee544e5dc8684ae39fa

Observation f71bc149-f084-4425-aa0f-4c289a64c7dc · outbound

This paper cites Do they want to cross? understanding pedestrian intention for behavior prediction.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Do they want to cross? understanding pedestrian intention for behavior prediction

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.194599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.690063Z digest=sha256:1fc41e7e9699807739358f7954159bde3f93b6d3167756dd37ca472f9bf8bfe9

Observation 2c1b9d46-d26d-4580-8608-ebde7765537c · outbound

This paper cites Long-term on-board prediction of people in traffic scenes under uncertainty.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Long-term on-board prediction of people in traffic scenes under uncertainty

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.170587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.695044Z digest=sha256:6a8d2d2a316f5214d12132f2d716a95a075382bed7b36601112ebe6afe4bd0ae

Observation b9b77231-fafb-471f-98f2-5c240693665c · outbound

This paper cites Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T18:07:42.699578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:07:42.699578Z digest=sha256:45e9853a88e4fc9ccf9a7e10838026173e8b470ce4decaba9f5aae9e304622cc

Observation aeca8c1e-a786-4016-b8ff-dd6a97a751c7 · outbound

This paper cites Pedestrian graph +: A fast pedestrian crossing prediction model based on graph convolutional networks.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Pedestrian graph +: A fast pedestrian crossing prediction model based on graph convolutional networks

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.143086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.704924Z digest=sha256:98ed565e75225a782b5b81ab59cede9c5dc74573dc17981b03061d1ea8c12346

Observation 311116e4-5ac7-40f2-abe1-d676710958e0 · outbound

This paper cites St cross- ingpose: A spatial-temporal graph convolutional network for skeleton- based pedestrian crossing intention prediction.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues St cross- ingpose: A spatial-temporal graph convolutional network for skeleton- based pedestrian crossing intention prediction

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.122366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.710647Z digest=sha256:4e7b8b1159edc080dfc1ff34fb004e2de4980efab8bdb033dce7462128b0700a

Observation 7eb3bf88-4791-473d-b572-37bd297b0ffd · outbound

This paper cites Pit: Progressive interaction transformer for pedestrian crossing intention prediction.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Pit: Progressive interaction transformer for pedestrian crossing intention prediction

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.102444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.715984Z digest=sha256:6538831aaae8b9bd13ea121acd965583065899815fa4dd02ab5b51a47326f744

Observation 3a2202ff-0452-4d8d-a250-c6769b3f62b7 · outbound

This paper cites IntFormer: Predicting pedestrian intention with the aid of the Transformer architecture.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues IntFormer: Predicting pedestrian intention with the aid of the Transformer architecture

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T18:07:42.721236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:07:42.721236Z digest=sha256:7afe4a76a7a3ffd45bdf4f6a3c71a0e76a793c4e8e94e9e2fd0307b741d4ed40

Observation 30013173-8e2d-4bd9-9052-761c46394a6d · outbound

This paper cites Multi-input fusion for practical pedestrian intention prediction.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Multi-input fusion for practical pedestrian intention prediction

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.082875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.726289Z digest=sha256:d13a28a35017a9618e9d39bba91774a832099931485e9d9b6ce2b6e1c148d148

Observation 9a4b6d00-7ac2-4067-a77d-6181dbaf8c2b · outbound

This paper cites Mcip: Multi-stream network for pedestrian crossing intention prediction.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Mcip: Multi-stream network for pedestrian crossing intention prediction

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.060484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.730697Z digest=sha256:aa07bb9ceece3df73ba5b4304c7908286b6cc9cab97f91c6652cf61b580e5be2

Observation ad55b0f5-960b-4119-95e3-3b05f7e8a084 · outbound

This paper cites GPT-4 Technical Report.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues GPT-4 Technical Report

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T18:07:42.735678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:07:42.735678Z digest=sha256:bc9ee850759694446395e8958989f9723c36342111b1550cb1a8b79a02a19583

Observation 56615001-b359-4991-8388-fa5ae81c44ea · outbound

This paper cites Visual instruction tuning.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Visual instruction tuning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T18:07:42.741551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:07:42.741551Z digest=sha256:d6222e771f9bf8bf5f8435cae605a8521936da80a886313c34a6650231daae15

Observation 06713f6c-bdea-4027-8be7-cbf2fef2493f · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues LLaMA: Open and Efficient Foundation Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T18:07:42.746267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:07:42.746267Z digest=sha256:4453c44ec1f354dabb2f91215533acde249de9672779de779913ad4074c1b6fa

Observation 43118ef7-50b4-4739-b8ca-8ed0aa49908f · outbound

This paper cites an unresolved cited work.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-15T18:07:43.028183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.754285Z digest=sha256:7b57a1c108326ad6ee7057e87976967a6701ccf3319eb90183c92babdf253b53

Observation d9e2c354-7181-4304-a8fd-b73f4f21bf68 · outbound

This paper cites GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-15T18:07:42.835595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.759290Z digest=sha256:02a0eed9109ca5b38d9e4135e4f791ea418c38895af3136df5a9ff796e065211

Observation 8d40db08-b0ec-49b7-b8bf-882c2f8f91a9 · outbound

This paper cites Predicting pedestrian crossing intention with feature fusion and spatio-temporal attention.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Predicting pedestrian crossing intention with feature fusion and spatio-temporal attention

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:43.005860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.765387Z digest=sha256:bc71e50dad5cbb0418b330e1c7fd6729a15bbfcde2027b4f9a6816bfc6722b0e

Observation c78d25c9-d830-4a76-bf63-dc32538967d9 · outbound

This paper cites Benchmark for evaluating pedestrian action prediction.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Benchmark for evaluating pedestrian action prediction

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T18:07:42.770137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:07:42.770137Z digest=sha256:ad932bc23e9a4ad39d6db7feb824faa6422eea0fa74931fdda7fa6e9717360a7

Observation b0427b0a-b3a7-4748-ac8c-3159ed965c5c · outbound

This paper cites ”Role play with large language models.” Nature 623, no.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues ”Role play with large language models.” Nature 623, no

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:42.965768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.775070Z digest=sha256:8d4b1cee572c167d9cbc662405b6fc122c625042153d23fdae2871fe0e14922d

Observation 035527af-9384-47f2-bef9-3b18660b9c96 · outbound

This paper cites ”Towards revealing the mystery behind chain of thought: a theoretical perspective.” Advances in Neural Information Processing Systems 36 (2023): 70757-70798.

Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues ”Towards revealing the mystery behind chain of thought: a theoretical perspective.” Advances in Neural Information Processing Systems 36 (2023): 70757-70798

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:07:42.949345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:07:42.779884Z digest=sha256:7910b8d79eb712c8f7ec6ce6fe296fad4a85ae7034318918a5f8b6f455819816

Pith citing papers

No inbound Pith citation observations are available.