Zhiwen Mo — accepted AI-conference papers

2026

TileLang: Bridge Programmability and Performance in Modern Neural Kernels

Lei Wang, Yu Cheng, Yining Shi, Zhiwen Mo, Zhengju Tang, Wenhao Xie +6

ICLR 2026oral

Modern AI algorithms increasingly adopt fused kernels for performance, but implementing them remains complex due to the lack of fine-grained control in existing compilers like Triton. We introduce TileLang, a controllable programming system for fused neural kernels. TileLang provides explicit tile-l…

Cited by 0 Source ↗code ↗Scholar ↗

2025

Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling

Hao Mark Chen, Guanxi Lu, Yasuyuki Okoshi, Zhiwen Mo, Masato Motomura, Hongxiang Fan

NeurIPS 2025poster

Test-time scaling (TTS) has proven effective in enhancing the reasoning capabilities of large language models (LLMs). Verification plays a key role in TTS, simultaneously influencing (1) reasoning performance and (2) compute efficiency, due to the quality and computational cost of verification. In t…

Cited by 0 Source ↗Scholar ↗