19 citations · 35 across the 15 of their papers we have counts for
4 papers · 1 filter
Self-Explained Keywords Empower Large Language Models for Code Generation
Lishui Fan, Mouxiang Chen, Zhongxin Liu
Large language models (LLMs) have achieved impressive performance in code generation. However, due to the long-tail distribution of LLMs' training data, low-frequency terms are typ…
B4: Towards Optimal Assessment of Plausible Code Solutions with Plausible Tests
Mouxiang Chen, Zhongxin Liu, He Tao +4
Selecting the best code solution from multiple generated ones is an essential task in code generation, which can be achieved by using some reliable validators (e.g., developer-writ…
VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
Mouxiang Chen, Lefei Shen, Zhuo Li +3
Foundation models have emerged as a promising approach in time series forecasting (TSF). Existing approaches either repurpose large language models (LLMs) or build large-scale time…
JumpCoder: Go Beyond Autoregressive Coder via Online Modification
Mouxiang Chen, Hao Tian, Zhongxin Liu +2
While existing code large language models (code LLMs) exhibit impressive capabilities in code generation, their autoregressive sequential generation inherently lacks reversibility.…