works on

From the 1 of 7 linked papers with an AI index.

activity
20242026
collaborators

7 papers

cs.AI2026

Meta-Task: Turning Terminal Task Synthesis into a Terminal Task for Scalable Agent Training

Zhihong Pan, Jiyuan He, Kai Zhang +5

The paper introduces Meta-Task, a framework that generates and verifies terminal tasks inside real container environments, enabling scalable training of terminal agents with high‑q…

cs.SE2026

SWE-Mutation: Can LLMs Generate Reliable Test Suites in Software Engineering?

Yuxuan Sun, Yuze Zhao, Yufeng Wang +6

Evaluating software engineering capabilities has become a core component of modern large language models (LLMs); however, the key bottleneck hindering further scaling lies not in t…

cs.AI2026

What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code

Yuze Zhao, Junpeng Fang, Lu Yu +6

Code has become a standard component of modern foundation language model (LM) training, yet its role beyond programming remains unclear. We revisit the claim that code improves rea…

cs.SE2025

Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor

Weibo Gao, Qi Liu, Rui Li +5

Programming Knowledge Tracking (PKT) aims to dynamically diagnose learners' mastery levels of programming knowledge based on their coding activities, facilitating more effective an…

cs.CL2025

Route to Reason: Adaptive Routing for LLM and Reasoning Strategy Selection

Zhihong Pan, Kai Zhang, Yuze Zhao +1

The inherent capabilities of a language model (LM) and the reasoning strategies it employs jointly determine its performance in reasoning tasks. While test-time scaling is regarded…

cs.AI2025

Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment

Yuze Zhao, Tianyun Ji, Wenjun Feng +6

The reasoning abilities are one of the most enigmatic and captivating aspects of large language models (LLMs). Numerous studies are dedicated to exploring and expanding the boundar…