3 papers
cs.CL2025
Teaching Your Models to Understand Code via Focal Preference Alignment
Jie Wu, Haoling Li, Xin Zhang +8
Preference learning extends the performance of Code LLMs beyond traditional supervised fine-tuning by leveraging relative quality comparisons. In existing approaches, a set of n ca…
cs.CL2025
GATE: Graph-based Adaptive Tool Evolution Across Diverse Tasks
Jianwen Luo, Yiming Huang, Jinxiang Meng +7
Large Language Models (LLMs) have shown great promise in tool-making, yet existing frameworks often struggle to efficiently construct reliable toolsets and are limited to single-ta…
cs.CL2024
DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models
Yiming Huang, Jianwen Luo, Yan Yu +8
We introduce DA-Code, a code generation benchmark specifically designed to assess LLMs on agent-based data science tasks. This benchmark features three core elements: First, the ta…