2 citations · 3 across the 9 of their papers we have counts for
6 papers · 1 filter
Plausible Is Not Enough: Trust and Evidence in AI-Authored Pull Request Review
Md Shamimur Rahman, Khairul Alam, Banani Roy +1
Code review is where AI-authored pull requests (AIPRs) must earn reviewer trust before integration, yet it is unclear whether reviewers apply the same criteria used for human-autho…
Who Pays the Review Cost? Triage, Fairness, and Accountability in AI-authored Pull Requests
Md Shamimur Rahman, Khairul Alam, Banani Roy +1
AI coding agents are moving from local code assistance into pull-based workflows, where generated contributions must be reviewed, explained, and maintained within existing project…
A Unified Model for Cross-Domain Clone Detection via Model Merging
Palash R. Roy, Banani Roy, Kevin A. Schneider +1
The growing diversity of code clone types, from syntactic copies to cross-language semantic clones to AI-generated duplicates, has created a fragmentation crisis in clone detection…
MergeSE: Post-Hoc Model Merging for Software Engineering Tasks Without Retraining
Palash R. Roy, Banani Roy, Kevin A. Schneider +1
Fine-tuned code models often behave as domain specialists and can degrade sharply under distribution shift: in our clone-detection setting, a model trained on same-language clones…
Carbon-Taxed Transformers: A Green Compression Pipeline for Overgrown Language Models
Ajmain Inqiad Alam, Palash Roy, Chanchal K. Roy +2
The accelerating adoption of Large Language Models (LLMs) in software engineering (SE) has brought with it a silent crisis: unsustainable computational cost. While these models dem…
Cuboids are canonically Ramsey
Benedict Randall Shaw
We say a set of points is canonically Ramsey if there is some set of points such that any colouring of , with any number of co…