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cs.AI2026
Beyond Correctness: Compute-Responsive Data Selection for Reasoning Model Post-Training
Liang He, Xiangyu Li, Yuxin Wang +4
Reasoning language models increasingly rely on test-time compute scaling, yet most existing work studies how to allocate inference computation while treating the model itself as fi…
cs.AI2026
LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model
Xiangyu Li, Tianyi Wang, Xi Cheng +5
Accurate classification of autonomous vehicle (AV) driving behaviors is critical for safety validation, performance diagnosis, and traffic integration analysis. However, existing a…