Jason Yik — accepted AI-conference papers

2026

QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture

Shvetank Prakash, Andrew Cheng, Arya Tschand, Mark Mazumder, Varun Gohil, Jeffrey Ma +21

ICML 2026poster

The field of computer architecture, which bridges high-level software abstractions and low-level hardware implementations, remains absent from current large language model (LLM) evaluations. To this end, we present QuArch (pronounced 'quark'), the first benchmark designed to facilitate the developme…

Cited by 0 Source ↗Scholar ↗

2023

VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning

Yu-Shun Hsiao, Siva Kumar Sastry Hari, Balakumar Sundaralingam, Jason Yik, Thierry Tambe, Charbel Sakr +2

IROS 2023poster

High-dimensional motion generation requires nu-merical precision for smooth, collision-free solutions. Typically, double-precision or single-precision floating-point (FP) formats are utilized. Using these for big tensors imposes a strain on the memory bandwidth provided by the devices and alters the…

Cited by 5 Source ↗Scholar ↗