6 citations · 12 across the 4 of their papers we have counts for
4 papers
Tracing the Thought of a Grandmaster-level Chess-Playing Transformer
Rui Lin, Zhenyu Jin, Guancheng Zhou +7
While modern transformer neural networks achieve grandmaster-level performance in chess and other reasoning tasks, their internal computation process remains largely opaque. Focusi…
Hard instance learning for quantum adiabatic prime factorization
Jian Lin, Zhengfeng Zhang, Junping Zhang +1
Prime factorization is a difficult problem with classical computing, whose exponential hardness is the foundation of Rivest-Shamir-Adleman (RSA) cryptography. With programmable qua…
Efficiently Training On-Policy Actor-Critic Networks in Robotic Deep Reinforcement Learning with Demonstration-like Sampled Exploration
Zhaorun Chen, Binhao Chen, Shenghan Xie +4
In complex environments with high dimension, training a reinforcement learning (RL) model from scratch often suffers from lengthy and tedious collection of agent-environment intera…
Exploration-efficient Deep Reinforcement Learning with Demonstration Guidance for Robot Control
Ke Lin, Liang Gong, Xudong Li +6
Although deep reinforcement learning (DRL) algorithms have made important achievements in many control tasks, they still suffer from the problems of sample inefficiency and unstabl…