390 citations · 488 across the 8 of their papers we have counts for
8 papers
Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries
Zelalem Gero, Chandan Singh, Yiqing Xie +6
Summarizing clinical text is crucial in health decision-support and clinical research. Large language models (LLMs) have shown the potential to generate accurate clinical text summ…
Position Paper: Agent AI Towards a Holistic Intelligence
Qiuyuan Huang, Naoki Wake, Bidipta Sarkar +13
Recent advancements in large foundation models have remarkably enhanced our understanding of sensory information in open-world environments. In leveraging the power of foundation m…
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning
Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee +4
Standard fine-tuning of large pre-trained language models (PLMs) for downstream tasks requires updating hundreds of millions to billions of parameters, and storing a large copy of…
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning
Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee +4
Standard fine-tuning of large pre-trained language models (PLMs) for downstream tasks requires updating hundreds of millions to billions of parameters, and storing a large copy of…
Deep Learning Based Text Classification: A Comprehensive Review
Shervin Minaee, Nal Kalchbrenner, Erik Cambria +3
Deep learning based models have surpassed classical machine learning based approaches in various text classification tasks, including sentiment analysis, news categorization, quest…
Guided Dialog Policy Learning without Adversarial Learning in the Loop
Ziming Li, Sungjin Lee, Baolin Peng +5
Reinforcement Learning (RL) methods have emerged as a popular choice for training an efficient and effective dialogue policy. However, these methods suffer from sparse and unstable…
Towards Coherent and Cohesive Long-form Text Generation
Woon Sang Cho, Pengchuan Zhang, Yizhe Zhang +5
Generating coherent and cohesive long-form texts is a challenging task. Previous works relied on large amounts of human-generated texts to train neural language models. However, fe…
Microsoft Dialogue Challenge: Building End-to-End Task-Completion Dialogue Systems
Xiujun Li, Yu Wang, Siqi Sun +3
This proposal introduces a Dialogue Challenge for building end-to-end task-completion dialogue systems, with the goal of encouraging the dialogue research community to collaborate…