Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-20T19:15:27.035840Z
Paper Citation Record · LEDGER
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment
As of 17 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2605.15654.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
63 of 63 outbound references displayed
- verified exact14
- verified fuzzy43
- unresolved4
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 8237d5ab-e979-4299-b654-1360e40e0a20 · outbound
This paper cites Waymo’s incidents: As of the end of 2024, the national highway traffic safety administration (nhtsa) had received 835 reports documenting 696 incidents involving waymo vehicles.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Waymo’s incidents: As of the end of 2024, the national highway traffic safety administration (nhtsa) had received 835 reports documenting 696 incidents involving waymo vehicles
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.068564Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 60e9da36-3ec3-4c8f-ac7f-0b52cd417a9f · outbound
This paper cites As of 2024, there have been 51 reported fatalities involving tesla’s autopilot function, with 44 verified by nhtsa or expert testimony.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment As of 2024, there have been 51 reported fatalities involving tesla’s autopilot function, with 44 verified by nhtsa or expert testimony
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.031981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 16adfc39-edd4-4078-b0cb-0942d7d5dd84 · outbound
This paper cites Performance limit evaluation strategy for automated driving systems.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Performance limit evaluation strategy for automated driving systems
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.080159Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 17454915-18e5-47c1-a322-44195d98e583 · outbound
This paper cites Risk and complexity assessment of autonomous vehicle testing scenarios.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Risk and complexity assessment of autonomous vehicle testing scenarios
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.002082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 23349652-c8d0-4897-930d-923830bf5c2d · outbound
This paper cites A survey on datasets for the decision making of autonomous vehicles.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment A survey on datasets for the decision making of autonomous vehicles
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:54.988038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 683f6714-a1d0-4380-8234-dab1dcfafdd1 · outbound
This paper cites A survey on safety-critical driving scenario generation—a methodological perspec- tive.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment A survey on safety-critical driving scenario generation—a methodological perspec- tive
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.041958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4b8e9789-7223-419b-b219-13dc2b87e646 · outbound
This paper cites Generative Modeling for Adversarial Lane-Change Scenarios.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Generative Modeling for Adversarial Lane-Change Scenarios
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:18:54.612941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 52cbe665-a0b7-4bef-bec6-aab9411a9851 · outbound
This paper cites Kinetic analysis and numerical tests of an adaptive car-following model for real-time traffic in its.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Kinetic analysis and numerical tests of an adaptive car-following model for real-time traffic in its
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.007545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f2a2924d-3438-453b-a676-f41c6f6811ba · outbound
This paper cites Advsim: Generating safety-critical scenarios for self- driving vehicles.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Advsim: Generating safety-critical scenarios for self- driving vehicles
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.011423Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a7b7a603-d7d2-4229-91a1-a61b44926125 · outbound
This paper cites Trafficgen: Learning to generate diverse and realistic traffic scenarios.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Trafficgen: Learning to generate diverse and realistic traffic scenarios
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.054638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8774a37e-d6a5-498d-bf86-20300c4a6bef · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment LLaMA: Open and Efficient Foundation Language Models
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T19:18:54.637158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5341ed57-5886-45d5-9ed1-9015387c5e6a · outbound
This paper cites INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:18:54.610001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 21e6ada7-e45c-4cee-9448-302fc1cae605 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T19:18:54.619274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4995bd05-0fdc-4cc9-88b2-5b433b807cc7 · outbound
This paper cites DeepSeek-V3 Technical Report.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment DeepSeek-V3 Technical Report
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T19:18:54.628313Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 025c5f2e-aa03-4f31-9093-9262d26b86fd · outbound
This paper cites Qwen2.5 Technical Report.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Qwen2.5 Technical Report
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T19:18:54.616307Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c66cde10-fea1-41c0-aeee-f869bcded9fc · outbound
This paper cites Language conditioned traffic generation.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Language conditioned traffic generation
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.003833Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6165da49-4d00-4c1d-991c-67f5d8581d09 · outbound
This paper cites Waymo simulated driving behavior in reconstructed fatal crashes within an autonomous vehicle operating domain.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Waymo simulated driving behavior in reconstructed fatal crashes within an autonomous vehicle operating domain
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.066596Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e8eaf50f-2372-4452-8ab7-73269bbc032b · outbound
This paper cites Surfelgan: Synthesizing realistic sensor data for autonomous driving.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Surfelgan: Synthesizing realistic sensor data for autonomous driving
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.036173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7d816d11-8832-4a96-b640-fcc61586aa85 · outbound
This paper cites Interactive critical scenario generation for autonomous vehicles testing based on in-depth crash data using reinforcement learning.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Interactive critical scenario generation for autonomous vehicles testing based on in-depth crash data using reinforcement learning
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.070438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5f566847-bf75-4f12-a095-6b1f3a187003 · outbound
This paper cites Adaptive stress testing of airborne collision avoidance systems.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Adaptive stress testing of airborne collision avoidance systems
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.062886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f6efff3b-1052-4bc0-a3db-c07e24006478 · outbound
This paper cites Generating adversarial driving scenarios in high-fidelity simulators.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Generating adversarial driving scenarios in high-fidelity simulators
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.052757Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 113581a0-c7a6-4bc3-b68d-e39778c3516b · outbound
This paper cites Structured domain randomization: Bridging the reality gap by context-aware synthetic data.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Structured domain randomization: Bridging the reality gap by context-aware synthetic data
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.050965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4097a700-98bb-4f8c-bf33-3e9eaa133d31 · outbound
This paper cites Adversarial safety-critical scenario generation using naturalistic human driving priors.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Adversarial safety-critical scenario generation using naturalistic human driving priors
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.061050Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6a045f8e-9390-43f3-a361-a20348598f8a · outbound
This paper cites King: Generating safety-critical driving scenarios for robust imitation via kinematics gradients.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment King: Generating safety-critical driving scenarios for robust imitation via kinematics gradients
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.074629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f20814db-9e4f-475d-a2d5-be3f848d0bbd · outbound
This paper cites LLM-attacker: Enhancing Closed-loop Adversarial Scenario Generation for Autonomous Driving with Large Language Models.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment LLM-attacker: Enhancing Closed-loop Adversarial Scenario Generation for Autonomous Driving with Large Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:18:54.643336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 684b69cc-493c-447a-9a70-29848e998204 · outbound
This paper cites FREA: Feasibility-Guided Generation of Safety-Critical Scenarios with Reasonable Adversariality.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment FREA: Feasibility-Guided Generation of Safety-Critical Scenarios with Reasonable Adversariality
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:18:54.646301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a9ae4fbb-0fa6-4eb6-8c47-009bed21d0bf · outbound
This paper cites Ontology based scene creation for the development of automated vehicles.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Ontology based scene creation for the development of automated vehicles
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.016700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2ea9af57-f95b-41a2-a5f6-6cadb82dfde8 · outbound
This paper cites Summit: A simulator for urban driving in massive mixed traffic.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Summit: A simulator for urban driving in massive mixed traffic
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.047558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 39030f91-b12c-4af1-b37b-cd4ae4b671f8 · outbound
This paper cites Scenario factory: Creating safety-critical traffic scenarios for automated vehicles.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Scenario factory: Creating safety-critical traffic scenarios for automated vehicles
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.059018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 224a11b9-e7dd-44c6-a089-3145f7cc4ddf · outbound
This paper cites TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-08-11T01:19:49.341731Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2faa46a5-5dcc-4474-b2a1-5b458190e393 · outbound
This paper cites LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos
Reference 31
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T19:18:54.625566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 150711df-82df-43fc-98c1-4a8f04b54ac2 · outbound
This paper cites Optimizing autonomous driving for safety: A human-centric approach with llm-enhanced rlhf.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Optimizing autonomous driving for safety: A human-centric approach with llm-enhanced rlhf
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.039960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b32448d6-fba0-43a3-ab49-16cea7bd2b53 · outbound
This paper cites Chatscene: Knowledge-enabled safety- critical scenario generation for autonomous vehicles.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Chatscene: Knowledge-enabled safety- critical scenario generation for autonomous vehicles
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.029895Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0ee9255c-efb2-42d1-8c9b-c030fb17a63e · outbound
This paper cites Text2Scenario: Text-Driven Scenario Generation for Autonomous Driving Test.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Text2Scenario: Text-Driven Scenario Generation for Autonomous Driving Test
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:18:54.640361Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1c71aa65-e701-4432-bd11-2f6ba3de743b · outbound
This paper cites Promptable Closed-loop Traffic Simulation.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Promptable Closed-loop Traffic Simulation
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:18:54.631524Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ec3d3fd8-e185-4349-894c-b4a03efaae9e · outbound
This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T19:18:54.634269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation df61a42f-ef4f-4f84-8240-ca1a92bb9b8a · outbound
This paper cites Billion-scale similarity search with gpus.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Billion-scale similarity search with gpus
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.005775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8bb46921-4725-46c3-a193-db0a2af36823 · outbound
This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Self-Consistency Improves Chain of Thought Reasoning in Language Models
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T19:18:54.603842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7b295016-b34c-46ad-ac40-6b0713b1a61a · outbound
This paper cites The primacy bias in deep reinforcement learning.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment The primacy bias in deep reinforcement learning
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.038073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 60c117bb-fdad-404a-9e46-fbda5afcd808 · outbound
This paper cites Cat: Closed-loop adversarial training for safe end-to-end driving.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Cat: Closed-loop adversarial training for safe end-to-end driving
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.076660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a7dbc24d-b602-46c5-be47-37d3cf97cf85 · outbound
This paper cites Low-Dissipation Data Bus via Coherent Quantum Dynamics.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Low-Dissipation Data Bus via Coherent Quantum Dynamics
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:18:54.607178Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cae28779-32d2-4633-a9e3-3b6201222b4e · outbound
This paper cites Gpt-5 technical overview.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Gpt-5 technical overview
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.043772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a461551e-8fd0-488d-a582-287ad54a9b1d · outbound
This paper cites Claude 4 model family.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Claude 4 model family
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.064590Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 95a30233-7b98-421b-9154-05cbffff90cf · outbound
This paper cites CARLA: An open urban driving simulator.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment CARLA: An open urban driving simulator
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.020393Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4bcf2767-bec3-42b9-9cc8-d8ebfc782387 · outbound
This paper cites ego vehicle going straight with background vehi- cle turning left.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment ego vehicle going straight with background vehi- cle turning left
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:54.994627Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0924529e-88a3-4d08-aa2d-d626bfd2db2f · outbound
This paper cites The integration process is designed as follows: a) Data-driven Insight Extraction.:The ego vehicle’s motion patterns are summarized by parsing the processed JSON trajectory data.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment The integration process is designed as follows: a) Data-driven Insight Extraction.:The ego vehicle’s motion patterns are summarized by parsing the processed JSON trajectory data
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:54.990449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 26002ca1-e119-4e3e-8a71-cdb60c7f86a3 · outbound
This paper cites turn left.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment turn left
Reference 47
- Resolution
- malformed identifier
- raw_fallback, observed 2026-05-20T19:18:54.998579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 585a6783-7963-493a-8003-6edbbf04db21 · outbound
This paper cites an unresolved cited work.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Unresolved cited work
Reference 48
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T19:18:55.018496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e33cd1ea-d281-48c4-b360-e43c7ef63f51 · outbound
This paper cites Semantic consistency must be strictly maintained—no changes to the original intent are allowed.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Semantic consistency must be strictly maintained—no changes to the original intent are allowed
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.027541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ffb81405-56ac-431b-9bbc-37e1ccdd39b3 · outbound
This paper cites It is not necessary to specify the full road network structure; instead, provide a template that references reading from an .osm map.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment It is not necessary to specify the full road network structure; instead, provide a template that references reading from an .osm map
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:54.992687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1c8481dc-e2d7-42d6-9498-7722607c8c43 · outbound
This paper cites Each element in the DSL must have a clear one-to-one semantic correspondence to the narrative description.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Each element in the DSL must have a clear one-to-one semantic correspondence to the narrative description
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.022743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1cd51561-7b8f-4760-9696-4511a8afb8c9 · outbound
This paper cites description.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment description
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.014888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0ee5eebc-870b-4641-bb56-f0919521711a · outbound
This paper cites an unresolved cited work.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Unresolved cited work
Reference 53
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T19:18:55.000217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7d8095af-202b-487e-bfd4-6fa99bbf5a3b · outbound
This paper cites When creating scenario representations, please prioritize choosing from existing elements.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment When creating scenario representations, please prioritize choosing from existing elements
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:54.996712Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e06579fe-ecd4-45d4-a349-a14c9ddc09e8 · outbound
This paper cites •Syntax alignment checking: a) Ensure semantic consistency between the scenario description and generated scenario representation.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment •Syntax alignment checking: a) Ensure semantic consistency between the scenario description and generated scenario representation
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.056947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 832b02b0-95bd-4cfe-adec-132d961aefd6 · outbound
This paper cites (generated geometry snippet).
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment (generated geometry snippet)
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.078420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7a3a24c9-30c4-4f8d-bf61-aa15945025fe · outbound
This paper cites The overall workflow for DSL-to-Python code generation, including retrieval, prompt construction, and iterative debugging, is illustrated in Figure 8.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment The overall workflow for DSL-to-Python code generation, including retrieval, prompt construction, and iterative debugging, is illustrated in Figure 8
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.072456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c43d1ded-6027-4372-9879-7d919b374140 · outbound
This paper cites DSL code block b.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment DSL code block b
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.025449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 13b3d88f-1454-4352-a00e-2c927e26dd45 · outbound
This paper cites an unresolved cited work.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Unresolved cited work
Reference 59
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T19:18:55.013122Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4aa7c928-2a2c-437f-a722-77c635ca49e8 · outbound
This paper cites an unresolved cited work.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment Unresolved cited work
Reference 60
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T19:18:55.049188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 04591f0b-b914-499c-858a-6083b7b51866 · outbound
This paper cites open- closed.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment open- closed
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.033980Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9815cb23-43d7-427f-b2e9-777acc7a9bb5 · outbound
This paper cites 2)Instructions for Code Generation: •Preserve all logic encoded in the DSL behaviors without truncation.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment 2)Instructions for Code Generation: •Preserve all logic encoded in the DSL behaviors without truncation
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.045724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation df9bf61e-3a82-4db5-8fb7-2979122f0c89 · outbound
This paper cites 4)DSL Embedding: •Include the full DSL content within the prompt, properly formatted as a code block.
PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment 4)DSL Embedding: •Include the full DSL content within the prompt, properly formatted as a code block
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T19:18:55.009367Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.