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cs.CL2024
SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning
Yangruibo Ding, Jinjun Peng, Marcus J. Min +3
Code Large Language Models (Code LLMs) have excelled at tasks like code completion but often miss deeper semantics such as execution effects and dynamic states. This paper aims to…
cs.CL2024
A Survey of Useful LLM Evaluation
Ji-Lun Peng, Sijia Cheng, Egil Diau +4
LLMs have gotten attention across various research domains due to their exceptional performance on a wide range of complex tasks. Therefore, refined methods to evaluate the capabil…