1 citations · 1 across the 4 of their papers we have counts for
5 papers
Multi-Source and Cross-Scenario Strategy-Guided Code Optimization
Yuwei Zhao, Qianyu Xiao, Ye Cui +2
Automated code optimization improves program performance by refactoring source code, and recent studies use LLMs to generate optimization patches. The newest approaches are strateg…
Tongyi DeepResearch Technical Report
Tongyi DeepResearch Team, Baixuan Li, Bo Zhang +54
We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking research tasks. To incentivize autonomous…
SemOpt: LLM-Driven Code Optimization via Rule-Based Analysis
Yuwei Zhao, Yuan-An Xiao, Qianyu Xiao +2
Automated code optimization improves program performance through refactoring, and recent studies leverage LLMs for this purpose. Existing approaches mine optimization commits from…
Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems
Yuhan Cao, Zian Chen, Kun Quan +17
Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, capable of tackling complex tasks during inference. However, the extent to which LLMs can…
Chart-HQA: A Benchmark for Hypothetical Question Answering in Charts
Xiangnan Chen, Yuancheng Fang, Qian Xiao +5
Multimodal Large Language Models (MLLMs) have garnered significant attention for their strong visual-semantic understanding. Most existing chart benchmarks evaluate MLLMs' ability…