Paper Title Number 1
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, 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).
Download Paper | Download Slides
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 in arXiv preprint arXiv:2509.19128, 2025
We present PipelineRL, a fully pipelined on-policy reinforcement learning stack for large language models that keeps accelerators saturated without generating stale, off-policy trajectories. The system overlaps rollout, preference modeling, and policy updates to deliver up to 2× faster convergence on long-context reasoning benchmarks while retaining stability guarantees for PPO-style algorithms.
Recommended citation: Alexandre Piché, Ehsan Kamalloo, Rafael Pardinas, Xiaoyin Chen, Dzmitry Bahdanau. (2025). "PipelineRL: Faster On-policy Reinforcement Learning for Long Sequence Generation." arXiv preprint arXiv:2509.19128.
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