Fine-tuned LLaMA-based LLM agents with online reinforcement learning (PPO) in a text based multi-step environment (BabyAI-Text). Investigated the impact of encouraging “reasoning-before-action”. In this simple setting, reasoning-before-action did not improve sample efficiency but provided interpretability advantages, and we also observed an interesting “reasoning collapse” phenomenon.
Trained a deep Q-learning agent for stock portfolio optimization. Benchmarked against mean-variance and Sharpe-ratio baselines, with comparable or superior returns in test scenarios.
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
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Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
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Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
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Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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