26 citations · 73 across the 22 of their papers we have counts for
5 papers · 1 filter
Certainty Is Not Just Correctness: Rethinking Token-Level Certainty in LLM Reasoning
Yunfan Zhou, Ye Zhu, Zhihai Wang +3
Token-level certainty is widely used as a proxy for correctness in LLM training and inference. However, the performance of certainty-based methods depends both on the information i…
FSAN: Flow State Attention Network for Aerodynamic Prediction
Wenxuan Jin, Jianguo Yao, Haibing Guan +1
Accurate aerodynamic prediction is critical for designing fuel-efficient and safe transportation systems such as aircraft and automobiles, yet traditional computational fluid dynam…
InSituMeasure: Probing Situated Measurement Grounding in Industrial Scenes with Multimodal Large Language Models
Chao Shen, Xinyuan Li, Yunfan Zhou +4
For trained operators, gauge reading requires little specialized knowledge, low cognitive effort, and high repeatability. Yet Multimodal Large Language Models (MLLMs) remain unreli…
FPGAgent: An LLM-Assisted Framework for Autonomous HLS Code Generation and Verification in FPGA Environments
Tianyu Wang, Wenjie Wang, Jianguo Yao +2
Large language models (LLMs) have shown substantial promise for high-level synthesis (HLS) code generation, but most existing approaches validate only simulation or synthesis resul…
HIERA: Workload-Aware Planning Across Implementation Spaces for GPU Kernel Optimization
Jinghao Wang, Qiqi Gu, Chenpeng Wu +3
High-performance GPU kernels underpin modern deep learning and scientific computing. As workloads become increasingly diverse and GPU hardware evolves rapidly, developing efficient…