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Theorem Prover as a Judge for Synthetic Data Generation
Joshua Ong Jun Leang, Giwon Hong, Wenda Li +1
The demand for synthetic data in mathematical reasoning has increased due to its potential to enhance the mathematical capabilities of large language models (LLMs). However, ensuri…
CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning
Joshua Ong Jun Leang, Aryo Pradipta Gema, Shay B. Cohen
Mathematical reasoning remains a significant challenge for large language models (LLMs), despite progress in prompting techniques such as Chain-of-Thought (CoT). We present **Chain…
Integrating Counterfactual Simulations with Language Models for Explaining Multi-Agent Behaviour
Bálint Gyevnár, Christopher G. Lucas, Stefano V. Albrecht +1
Autonomous multi-agent systems (MAS) are useful for automating complex tasks but raise trust concerns due to risks such as miscoordination or goal misalignment. Explainability is v…