1.5k citations · 5.2k across the 127 of their papers we have counts for
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Secrets of RLHF in Large Language Models Part II: Reward Modeling
Binghai Wang, Rui Zheng, Lu Chen +24
Reinforcement Learning from Human Feedback (RLHF) has become a crucial technology for aligning language models with human values and intentions, enabling models to produce more hel…
The Rise and Potential of Large Language Model Based Agents: A Survey
Zhiheng Xi, Wenxiang Chen, Xin Guo +26
For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI a…
Towards Collaborative Question Answering: A Preliminary Study
Xiangkun Hu, Hang Yan, Qipeng Guo +3
Knowledge and expertise in the real-world can be disjointedly owned. To solve a complex question, collaboration among experts is often called for. In this paper, we propose CollabQ…
Pre-Trained Models: Past, Present and Future
Xu Han, Zhengyan Zhang, Ning Ding +21
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI). Owing to sophis…
Neural Arithmetic Expression Calculator
Kaiyu Chen, Yihan Dong, Xipeng Qiu +1
This paper presents a pure neural solver for arithmetic expression calculation (AEC) problem. Previous work utilizes the powerful capabilities of deep neural networks and attempts…
Exploring Shared Structures and Hierarchies for Multiple NLP Tasks
Junkun Chen, Kaiyu Chen, Xinchi Chen +2
Designing shared neural architecture plays an important role in multi-task learning. The challenge is that finding an optimal sharing scheme heavily relies on the expert knowledge…
Meta Multi-Task Learning for Sequence Modeling
Junkun Chen, Xipeng Qiu, Pengfei Liu +1
Semantic composition functions have been playing a pivotal role in neural representation learning of text sequences. In spite of their success, most existing models suffer from the…