5 citations · 7 across the 4 of their papers we have counts for
4 papers
Learning with Rare Success but Rich Feedback via Reflection-Enhanced Self-Distillation
Yuwei Zhang, Sha Li, Changlong Yu +9
Enabling Large Language Models (LLMs) to continuously improve from environmental interactions is a central challenge in post-training. While on-policy self-distillation offers a pr…
APAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model for Noisy Labels and Long-tailed Learning
Sunyi Chi, Bo Dong, Yiming Xu +2
Practical natural language processing (NLP) tasks are commonly long-tailed with noisy labels. Those problems challenge the generalization and robustness of complex models such as D…
Inducing Cooperation via Team Regret Minimization based Multi-Agent Deep Reinforcement Learning
Runsheng Yu, Zhenyu Shi, Xinrun Wang +5
Existing value-factorized based Multi-Agent deep Reinforce-ment Learning (MARL) approaches are well-performing invarious multi-agent cooperative environment under thecen-tralized t…
Predictive Learning: Using Future Representation Learning Variantial Autoencoder for Human Action Prediction
Yu Runsheng, Shi Zhenyu, Ma Qiongxiong +1
The unsupervised Pretraining method has been widely used in aiding human action recognition. However, existing methods focus on reconstructing the already present frames rather tha…