5 papers
The Cold-Start Safety Gap in LLM Agents
Chung-En Sun, Linbo Liu, Tsui-Wei Weng
Are tool-calling LLM agents equally safe throughout a conversation? We discover they are not: agents are most vulnerable at the very start of a session and become substantially saf…
MigrationBench: Repository-Level Code Migration Benchmark from Java 8
Linbo Liu, Xinle Liu, Qiang Zhou +8
With the rapid advancement of powerful large language models (LLMs) in recent years, a wide range of software engineering tasks can now be addressed using LLMs, significantly enhan…
CLEAR: Context Augmentation from Contrastive Learning of Experience via Agentic Reflection
Linbo Liu, Guande Wu, Han Ding +7
Large language model agents rely on effective model context to obtain task-relevant information for decision-making. Many existing context engineering approaches primarily rely on…
QualityFlow: An Agentic Workflow for Program Synthesis Controlled by LLM Quality Checks
Yaojie Hu, Qiang Zhou, Qihong Chen +6
We introduce QualityFlow, a dynamic agentic workflow for program synthesis. Given the English description of a programming problem and a set of unit tests, the model's goal is to s…
CodeFort: Robust Training for Code Generation Models
Yuhao Zhang, Shiqi Wang, Haifeng Qian +8
Code generation models are not robust to small perturbations, which often lead to incorrect generations and significantly degrade the performance of these models. Although improvin…