6 papers
Coding Agents Don't Know When to Act
Thibaud Gloaguen, Niels Mündler, Mark Müller +2
Coding agents are increasingly deployed to autonomously maintain software, including to resolve user-reported issues: a bug report comes in and the agent creates a patch to address…
CodeTaste: Can LLMs Generate Human-Level Code Refactorings?
Alex Thillen, Niels Mündler, Veselin Raychev +1
LLM coding agents can generate working code, but their solutions often accumulate complexity, duplication, and architectural debt. Human developers address such issues through refa…
Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents?
Thibaud Gloaguen, Niels Mündler, Mark Müller +2
A widespread practice in software development is to tailor coding agents to repositories using context files, such as AGENTS.md. Although this practice is strongly encouraged by ag…
BaxBench: Can LLMs Generate Correct and Secure Backends?
Mark Vero, Niels Mündler, Victor Chibotaru +5
Automatic program generation has long been a fundamental challenge in computer science. Recent benchmarks have shown that large language models (LLMs) can effectively generate code…
BgGPT 1.0: Extending English-centric LLMs to other languages
Anton Alexandrov, Veselin Raychev, Dimitar I. Dimitrov +3
We present BgGPT-Gemma-2-27B-Instruct and BgGPT-Gemma-2-9B-Instruct: continually pretrained and fine-tuned versions of Google's Gemma-2 models, specifically optimized for Bulgarian…
Mitigating Catastrophic Forgetting in Language Transfer via Model Merging
Anton Alexandrov, Veselin Raychev, Mark Niklas Müller +3
As open-weight large language models (LLMs) achieve ever more impressive performances across a wide range of tasks in English, practitioners aim to adapt these models to different…