7 papers
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…
To Think or Not to Think: Allocating Reasoning Where It Helps
Zhengdong He, Yunfan Zhou, Jianguo Yao +2
Reinforcement learning (RL) has proven effective in enhancing the reasoning performance of large language models (LLMs), particularly in complex mathematical and programming tasks.…
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…
FWeb3: A Practical Incentive-Aware Federated Learning Framework
Peishen Yan, Shuang Liang, Yang Hua +9
Federated learning (FL) enables collaborative model training over distributed private data. However, sustaining open participation requires incentive mechanisms that compensate con…
Do We Need Tensor Cores for Stencil Computations?
Qiqi Gu, Chenpeng Wu, Heng Shi +2
Stencil computation constitutes a cornerstone of scientific computing, serving as a critical kernel in domains ranging from fluid dynamics to weather simulation. While stencil comp…
STRCMP: Integrating Graph Structural Priors with Language Models for Combinatorial Optimization
Xijun Li, Jiexiang Yang, Jinghao Wang +3
Combinatorial optimization (CO) problems, central to operation research and theoretical computer science, present significant computational challenges due to their NP-hard nature.…