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20242026
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cs.SE2026

Making Embodied AI Reliable: A Community Agenda from Testing to Formal Verification

Xi Zheng, Dulanga Weerakoon, Yintong Huo +8

Embodied AI systems are increasingly deployed in open-world environments, yet ensuring their reliability remains a fundamental challenge. Drawing on discussions from the AAAI'26 Br…

cs.SE2026

CONCUR: Benchmarking LLMs for Concurrent Code Generation

Jue Huang, Tarek Mahmud, Corina Pasareanu +1

Leveraging Large Language Models (LLMs) for code generation has increasingly emerged as a common practice in the domain of software engineering. Relevant benchmarks have been estab…

cs.SE2025

Agentic AI Software Engineers: Programming with Trust

Abhik Roychoudhury, Corina Pasareanu, Michael Pradel +1

Large Language Models (LLMs) have shown surprising proficiency in generating code snippets, promising to automate large parts of software engineering via artificial intelligence (A…

cs.SE2025

Worst-Case Symbolic Constraints Analysis and Generalisation with Large Language Models

Daniel Koh, Yannic Noller, Corina S. Pasareanu +2

Large language models (LLMs) have demonstrated strong performance on coding tasks such as generation, completion and repair, but their ability to handle complex symbolic reasoning…

cs.SE2025

Enhancing LLM Code Generation with Ensembles: A Similarity-Based Selection Approach

Tarek Mahmud, Bin Duan, Corina Pasareanu +1

Ensemble learning has been widely used in machine learning to improve model robustness, accuracy, and generalization, but has not yet been applied to code generation tasks with lar…