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Claude Code-Driving Scenario Mining for the Argoverse 2 Challenge

arXiv CS Tuesday 09 June 2026, 04:00 UTC By Wei Deng, Caoshengzhe Xue, Shuaikun Liu, Zhaohong Liu, Mengshi Qi, Huadong Ma 1 min read
Key Points

Announce Type: new Abstract: We present our submission to the CVPR 2026 Argoverse 2 Scenario Mining Challenge. Our system uses a four-stage pipeline: (1) autonomous code generation via a Claude Code agent powered by GLM~5.1, (2) iterative training set screening with Timestamp Balanced Accuracy threshold 0.8 to curate few-shot examples, (3) semantic code review by a separate Claude Code session, and (4) Qwen3-VL scene-level verification to filter false positives.

arXiv:2606.09180v1 Announce Type: new Abstract: We present our submission to the CVPR 2026 Argoverse 2 Scenario Mining Challenge. Our system uses a four-stage pipeline: (1) autonomous code generation via a Claude Code agent powered by GLM~5.1, (2) iterative training set screening with Timestamp Balanced Accuracy threshold 0.8 to curate few-shot examples, (3) semantic code review by a separate Claude Code session, and (4) Qwen3-VL scene-level verification to filter false positives. We report results on the Argoverse 2 test set.
Claude Code-Driving Scenario Mining (PERSON) Claude (PERSON) Argoverse 2 (LOCATION)
Originally published by arXiv CS Read original →

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