5 citations · 6 across the 11 of their papers we have counts for
4 papers · 1 filter
An Empirical Study of Reasoning Steps in Thinking Code LLMs
Haoran Xue, Gias Uddin, Song Wang
Thinking Large Language Models (LLMs) generate explicit intermediate reasoning traces before final answers, potentially improving transparency, interpretability, and solution accur…
Stack Trace-Based Crash Deduplication with Transformer Adaptation
Md Afif Al Mamun, Gias Uddin, Lan Xia +1
Automated crash reporting systems generate large volumes of duplicate reports, overwhelming issue-tracking systems and increasing developer workload. Traditional stack trace-based…
TriagerX: Dual Transformers for Bug Triaging Tasks with Content and Interaction Based Rankings
Md Afif Al Mamun, Gias Uddin, Lan Xia +1
Pretrained Language Models or PLMs are transformer-based architectures that can be used in bug triaging tasks. PLMs can better capture token semantics than traditional Machine Lear…
PAGENT: Learning to Patch Software Engineering Agents
Haoran Xue, Gias Uddin, Song Wang
LLM Agents produce patches automatically to resolve an issue. However, they can generate inaccurate patches. Little is known about the root causes behind those failed patches or ho…