Papers by Spyridon Mouselinos

2 papers
A Simple, Yet Effective Approach to Finding Biases in Code Generation (2023.findings-acl)

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Challenge: Recent work shows that large language models can generate code on par with humans . however, data-driven approaches may not be sufficient for acquiring reasoning skills .
Approach: They propose a framework that automatically identifies subtle cues a code generation model might exploit . they propose an automated intervention mechanism reminiscent of adversarial testing .
Outcome: The proposed framework can be used as a data transformation technique during fine-tuning, acting as reversal strategy.
Beyond Lines and Circles: Unveiling the Geometric Reasoning Gap in Large Language Models (2024.findings-emnlp)

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Challenge: Recent advances in Large Language Models (LLMs) demonstrate increasing proficiency in complex mathematical and algorithmic tasks, yet their geometric reasoning skills are underexplored.
Approach: They propose a framework that enhances LLMs’ reasoning potential through a multi-agent system conducting internal dialogue.
Outcome: The proposed framework enhances LLMs’ reasoning potential through a multi-agent system conducting internal dialogue.

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