activity
20232026
most citedHumanity's Last Exam

23 citations · 32 across the 9 of their papers we have counts for

collaborators

12 papers

cs.SE2026

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…

cs.CR2026

SecPI: Secure Code Generation with Reasoning Models via Security Reasoning Internalization

Hao Wang, Niels Mündler, Mark Vero +3

Reasoning language models (RLMs) are increasingly used in programming. Yet, even state-of-the-art RLMs frequently introduce critical security vulnerabilities in generated code. Pri…

cs.SE2026

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…

cs.SE2026

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…

cs.CR2025

AutoBaxBuilder: Bootstrapping Code Security Benchmarking

Tobias von Arx, Niels Mündler, Mark Vero +2

As large language models (LLMs) see wide adoption in software engineering, the reliable assessment of the correctness and security of LLM-generated code is crucial. Notably, prior…

cs.LG2025

Constrained Decoding of Diffusion LLMs with Context-Free Grammars

Niels Mündler, Jasper Dekoninck, Martin Vechev

Large language models (LLMs) have shown promising performance across diverse domains. Many practical applications of LLMs, such as code completion and structured data extraction, r…