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Paper Citation Record · LEDGER

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner

As of 19 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2412.18086.

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

pith.paper-citation-record.v1
2412.18086 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:06:16.554760Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

52 of 52 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved43
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8cb3ab6a-fca9-41d8-954b-87ec79bc2c82 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner , " * write output.state after.block = add.period write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:15.469246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:15.469246Z digest=sha256:bb46b1e51116053c8858d0ea34e1453c14deb2a073e6b3989e652382a832e9fe

Observation ab6f8648-59c0-45c6-87dc-f70c696d4bab · outbound

This paper cites write newline.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:15.504751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:15.504751Z digest=sha256:6ccb47d37e302e797d387d58e81d6531011cb4584571dfce8f94cbc4704640fc

Observation 67a99219-1fb5-4334-a9c2-ab48c8fea5b8 · outbound

This paper cites GPT-4 Technical Report.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner GPT-4 Technical Report

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:15.554758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:15.554758Z digest=sha256:fa70143d00cd1002e339de81ec2be63dd64a3c9008b784f49b1a50f9de871e4e

Observation 9f786546-1fab-4890-afc2-30cf8d7391dd · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.254285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.604760Z digest=sha256:a2c2cca9cd47e3bed7e7b277a059752edb6a07390e78c2dfbad30656117a8aed

Observation 6280a0d2-369a-4d56-b141-698158849eae · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.235963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.664755Z digest=sha256:70811f66f408694ac7f3e492db037bfd97eef36cff9340293131df7e5168d531

Observation efc033c2-175f-45d4-8764-28eb4edcb248 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.216322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.671658Z digest=sha256:3786f55dfc43bfe570031af5deb2c905a8cf924093f30fc4b31ca89e11c5693d

Observation dda5670a-590d-49dd-a3fd-cb65a3fe82e1 · outbound

This paper cites TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-08-11T05:06:16.987714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.677624Z digest=sha256:9321fc1b49c818e86fd0856ef1e67c50096a51929b07ee9392055b2de5b71009

Observation 603ca4ad-3bd8-48de-8b80-3d63a74efc0a · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.202496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.696088Z digest=sha256:4fd28273bf944c0dee02c64d88cdd6660e9cd8f09eede3d6eac1057ba78dcf85

Observation 041dc67e-9b34-427d-82f4-8f2ebfa9f10d · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.187692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.719638Z digest=sha256:320691fe342b7ce8b3b8ad94330049d37ab518a26a9d4d8171358cd6a2457e52

Observation 0c7e3901-6d36-4985-9b36-29de59270189 · outbound

This paper cites H.; Vora, S.; Liong, V.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner H.; Vora, S.; Liong, V

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:18.157490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.756126Z digest=sha256:2ee3c45b85e156e107c9c6635c9a48435f0075c2e8142b68f618a9122b214ed9

Observation 82262fbf-c3d9-41a8-827d-801dbf27ff7a · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.112036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.770049Z digest=sha256:98f82d3cbcbd4ea9a97762d5dada7af33fba6085d38933c378ba79e94ecafcd5

Observation 01eb3003-48b9-4c79-b8dd-50018a993206 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.081337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.819457Z digest=sha256:d54a3906f8b3686e6ef346d057b050956e9f73427f953627642e174d6edfd29b

Observation 5aaac2cf-0b3b-46fe-bcd8-cc2e69e61707 · outbound

This paper cites Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:15.854754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:15.854754Z digest=sha256:81ccfe4ef8cfc03b12504c498a47240935bfcc54f425ea23348543b3d9ec09e7

Observation d0eb02f2-40d0-46d9-a264-994ec23e4b60 · outbound

This paper cites TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:15.874829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:15.874829Z digest=sha256:0a09a87e4b4ba8247f164a1d824eb48acf2dbbdcbe2aad253127a5e220174eff

Observation 1a6c60a1-f374-43de-97b0-ebfa145c8d1a · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.052446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.894780Z digest=sha256:04a802c5132f6d2f297100c487b794a04ee21e218a2edb8e9df994751799d1f1

Observation 4d94e31b-4a3c-4f5a-9ec3-dfaea5c7b8ba · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:15.917192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:15.917192Z digest=sha256:1298ab02e03f7bbe29ba942be3fbf7421dd8018b25f3a1cae4dbc5688cd2e612

Observation 2eccfa8d-c5dd-4cb6-9cdf-46b6fce1d65e · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:18.008041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.944750Z digest=sha256:20684ee7a018e525bda5282acd9f9c8fda83dce226cdf57e23ca5aa8f6822b72

Observation e8643bbe-9073-4325-93b2-a3a9b1a63c9d · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.994135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:15.984836Z digest=sha256:48bf7177e733faa471510886763327f6b3e2ed2b0cc31304acc6c880a22a61b5

Observation 26dd2979-a1c4-4fa9-949f-e7e090b0faa2 · outbound

This paper cites J.; Dreossi, T.; Ghosh, S.; Yue, X.; Sangiovanni-Vincentelli, A.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner J.; Dreossi, T.; Ghosh, S.; Yue, X.; Sangiovanni-Vincentelli, A

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:17.982258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.024756Z digest=sha256:0e5cc9fd4b5358afc180d72aae41486af310b211b4f4e45a1b47bf6a2ce64fd7

Observation a22d1f57-c758-472e-a18a-4dd219a05a02 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.969713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.041921Z digest=sha256:006e0138ca2b97553702f03a8613284d53148ef320ba014003ce82dc5c5252da

Observation 6e05b2cf-b383-4a84-8c58-0c0dcd765ec8 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.948775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.051755Z digest=sha256:36a4409f7a76aff7dfc6aa58e43f274ce824fd2254a17cb7da451a767fbcca44

Observation 45dd6860-7014-42a6-8d76-27422f208e0f · outbound

This paper cites Automatic Generation of Scenarios for System-level Simulation-based Verification of Autonomous Driving Systems.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Automatic Generation of Scenarios for System-level Simulation-based Verification of Autonomous Driving Systems

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:16.057427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:16.057427Z digest=sha256:7d4eb6a5b35ec83e0489d14640d5b8aed7222d5a582f426a5443d05d1ce96e7d

Observation 72eed1a7-734f-4f6a-a317-ded2fe211312 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.927161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.062978Z digest=sha256:6d7aa66d51310e6a2dac41be7406397dea8b45c936201a89e5f152b411990554

Observation ba03d4c6-f78f-45fe-a6fd-6f91e34af94e · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.912688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.072480Z digest=sha256:ac3741d154debb3ef261ddbe3d3c77e030bfe7a3524949bb04a433bc4ed1192e

Observation c0ce6a87-de51-482f-b198-feaa0836cdab · outbound

This paper cites E.; Schiegg, F.; and Z \"o llner, J.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner E.; Schiegg, F.; and Z \"o llner, J

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:17.898351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.080160Z digest=sha256:4e4050c3cf49923cfcfac671efd74c63fac711a1cf7328c9a0a51717cc3a4ad4

Observation 2f7c97d9-9d3e-4402-b028-8c9216d43c23 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.878783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.086165Z digest=sha256:21f39306c1d0ebb615500988633bf5cf8da70666ee2ef869359520ddab60e9ec

Observation e02f7ad0-a5e6-4bdb-83bb-73ec5f575226 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.861611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.093436Z digest=sha256:17282a7253eb753168fd4bd1b803c4e82b5e1698d3dd755a856ab3146e74bce2

Observation 91c1dc26-12f8-4f42-88e7-07e854cefb67 · outbound

This paper cites G.; Alexiadis, V.; and Zhang PE, L.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner G.; Alexiadis, V.; and Zhang PE, L

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:17.838159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.099992Z digest=sha256:a96fe29750e0b1b7a0b95f5d47d318f17af976c2e1a0b3cba52b080e63beaae3

Observation 1dc7ccd7-c1db-4c09-a19e-e37734f797ac · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.786113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.104629Z digest=sha256:36d8efd7b45cb62e1757c06c7a680a7a9eccde0c4fb68cc7eede5dcbe5a37691

Observation 55d44aaf-556d-405f-9586-1db26fd67c7d · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.722138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.109552Z digest=sha256:647e4635684361ebc2536aa1bc897dfc8ba2ba68247d46ed0a670b1c6a58e20c

Observation 7de94dcb-850b-4b42-91ab-e62bdc1ab491 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.697836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.113216Z digest=sha256:3611c4f7302b581ebb788f695f0d58bf9ce4d1538daf8b4f6b0166224ee641d7

Observation 3bf88f70-47b8-4c8f-8ec4-191abb57cda6 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.680074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.122337Z digest=sha256:02fe072003885716902f3590618896286d485d3eb8a3f30a25ac9da444bb5c41

Observation f2d49de0-84cc-449c-ad73-dc12b9c0a1ea · outbound

This paper cites M.; Feng, L.; Liu, Z.; Duan, C.; Mo, W.; and Zhou, B.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner M.; Feng, L.; Liu, Z.; Duan, C.; Mo, W.; and Zhou, B

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:17.661145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.129642Z digest=sha256:4b683582f1095f06c211da950cafa713f67c22cccbe3397a08368405a62b2c76

Observation 71187d2e-af30-4092-8930-19fcf9e50d38 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.643227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.134063Z digest=sha256:237188714dd24e5932c1815609e7ed3c97ab034506d132074fef6d24f0648846

Observation 831938bb-b875-414a-9cc4-9411f70d2789 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.626415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.139656Z digest=sha256:19d077008f9fd6fd891987ace3d0ab0e2bfe16b7c8afbf6d8eea7b50869a3e4d

Observation 09774412-34e4-429e-95ce-5a764c9c2234 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.605134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.146080Z digest=sha256:9b45d2983d7636856ecb8c75943e3dfd7183f16de162d497bccf4539641b96e9

Observation 1254a778-22cd-4ef7-9b1d-0e6365044a80 · outbound

This paper cites Language Models are Few-Shot Learners.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Language Models are Few-Shot Learners

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:16.187281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:16.187281Z digest=sha256:78787eb53f2b6fb55f7a2c1a30094c9ac3dd35981de45dca73aab0844518062e

Observation 3aea2830-c810-4887-8341-e49c6feb874f · outbound

This paper cites Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:16.197154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:16.197154Z digest=sha256:b5d4447d3b9c95eb82d36dc5085add356f08d3cc612b382d4715ba389048eba2

Observation b7bdf07c-3f8f-440f-b05a-57cdacaacafc · outbound

This paper cites T.; ; et al.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner T.; ; et al

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:17.561157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f9bcac21-58be-4b96-9e42-6451f86eb6b4 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.544699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.268414Z digest=sha256:5aa01640d752a2b0dac078958ea0d63c0efd89c661e8946287163c30354020df

Observation a9fbc72a-927e-4e8a-af5d-a6f4b98d9ea6 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.502754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.294848Z digest=sha256:1455e0aa27df2a7f0f859255848ff73b415dfa4ed76392101d157de5d2d5cf97

Observation 0debe625-62cc-4df7-acb5-f53d8eb22d07 · outbound

This paper cites C.; Mirje, M.; Bikkannavar, K.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner C.; Mirje, M.; Bikkannavar, K

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:17.424767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.320738Z digest=sha256:6cae0cec0be8dd07e74cb3fb0c2fc71175f885e917c94546afe1d1d035150ac3

Observation 326b3f3c-4f5b-4c18-8116-cc0516b2177c · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.382775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.340696Z digest=sha256:3cc745b0f62f0f6afe8e1e0bf8858caae730392e5819d0e74e0263a92e32d0fa

Observation ca36c992-c4ce-4959-92bf-408f00ead9b7 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.314769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.362239Z digest=sha256:123ee9f1b9fe0326c0d917bcb9ce64b1fa140addc7f3bb9d3ddf0315eb62b90b

Observation b2880603-b679-408f-9f5c-5d33ee98960e · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.237685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.382255Z digest=sha256:02ebb70bce1e4d30d2b01955ac11fbdade7ff57aebeb9ee6c13034373156f029

Observation 802ecce5-3aa2-4890-b4e2-0f59d0adc73e · outbound

This paper cites Do Prompt-Based Models Really Understand the Meaning of their Prompts?.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Do Prompt-Based Models Really Understand the Meaning of their Prompts?

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:16.415532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:16.415532Z digest=sha256:61997fde92a405828cf5ad5a2c8c8517f4097bc49c2a9e892482406197d8adfd

Observation a7689427-e8f4-4cac-b1b7-15978dfba9d3 · outbound

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

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:16.425482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:16.425482Z digest=sha256:451c00a4886c70939bc93bfdcc38edccaa18dd68af2a0a4492c2559f0924c617

Observation 86f1de92-1bbb-4fa5-ab28-4b985a626417 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.175624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.454751Z digest=sha256:c712858fddbeffd640fd6a02e86d318e0e92ba04b8a74d14a11ee508d51765f9

Observation ba4f96f6-d447-4075-9e77-926e127ffe13 · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.146930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.472994Z digest=sha256:bd7b4b8b2b6b1c458617f40ba243b3bf2ac2a836cd42ef26fa5b763e454998df

Observation c4662c06-bdd9-4aea-bbec-0cb070264f64 · outbound

This paper cites J.; Luo, X.; and Wang, M.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner J.; Luo, X.; and Wang, M

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:06:17.106642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.504753Z digest=sha256:51fa507d3aa5e899258b57630cea0f1df0ebc4048ebe1b858fcc1f6b6e03c84f

Observation 7d089bbc-f8b7-4c3e-baec-53503094270a · outbound

This paper cites an unresolved cited work.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:06:17.032376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T05:06:16.515942Z digest=sha256:f7a9358c425713b585a2832ea1534d1b975a45166a93fcd14b578c5e0553c3d2

Observation 1602ceae-c879-4047-ad33-da2cc42e697a · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner Automatic Chain of Thought Prompting in Large Language Models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T05:06:16.554760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:06:16.554760Z digest=sha256:ea35015a61f41f3bbef8bce5794d14099d551a0a75152d07c33a3eb6b094f6a6

Pith citing papers

No inbound Pith citation observations are available.