10 citations · 11 across the 4 of their papers we have counts for
5 papers
Past, Future, All at Once: Mitigating Stability-Plasticity Dilemma via Post-hoc JANUS Rectification
Zhilong Zheng, Letian Tao, Yang Guan +7
Fine-tuning foundation models on new tasks inevitably suffer from catastrophic forgetting. While existing works attempt to mitigate this on the basis of parameter-efficient fine-tu…
STAPO: Stabilizing Reinforcement Learning for LLMs by Silencing Rare Spurious Tokens
Shiqi Liu, Zeyu He, Guojian Zhan +10
Reinforcement Learning (RL) has significantly improved large language model reasoning, but existing RL fine-tuning methods rely heavily on heuristic techniques such as entropy regu…
Hierarchical Feature-level Reverse Propagation for Post-Training Neural Networks
Ni Ding, Shuchang Wang, Lei He +2
End-to-end neural networks have become a dominant paradigm in autonomous driving, where reliable deployment requires controllable post-training adaptation and improved transparency…
Training Multi-layer Neural Networks on Ising Machine
Xujie Song, Tong Liu, Shengbo Eben Li +3
As a dedicated quantum device, Ising machines could solve large-scale binary optimization problems in milliseconds. There is emerging interest in utilizing Ising machines to train…
SEPT: Towards Efficient Scene Representation Learning for Motion Prediction
Zhiqian Lan, Yuxuan Jiang, Yao Mu +2
Motion prediction is crucial for autonomous vehicles to operate safely in complex traffic environments. Extracting effective spatiotemporal relationships among traffic elements is…