3 papers
cs.CL2025
Z1: Efficient Test-time Scaling with Code
Zhaojian Yu, Yinghao Wu, Yilun Zhao +2
Large Language Models (LLMs) can achieve enhanced complex problem-solving through test-time computing scaling, yet this often entails longer contexts and numerous reasoning token c…
cs.SE2024
HumanEval Pro and MBPP Pro: Evaluating Large Language Models on Self-invoking Code Generation
Zhaojian Yu, Yilun Zhao, Arman Cohan +1
We introduce self-invoking code generation, a new task designed to evaluate the progressive reasoning and problem-solving capabilities of LLMs. In this task, models are presented w…
cs.CV2024
ATP-LLaVA: Adaptive Token Pruning for Large Vision Language Models
Xubing Ye, Yukang Gan, Yixiao Ge +2
Large Vision Language Models (LVLMs) have achieved significant success across multi-modal tasks. However, the computational cost of processing long visual tokens can be prohibitive…