70 citations · 368 across the 47 of their papers we have counts for
16 papers · 1 filter
Quantization-Aware and Tensor-Compressed Training of Transformers for Natural Language Understanding
Zi Yang, Samridhi Choudhary, Siegfried Kunzmann +1
Fine-tuned transformer models have shown superior performances in many natural language tasks. However, the large model size prohibits deploying high-performance transformer models…
Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary A. Pardos +5
As AI systems continue to evolve, their rigorous evaluation becomes crucial for their development and deployment. Researchers have constructed various large-scale benchmarks to det…
An AMR-based Link Prediction Approach for Document-level Event Argument Extraction
Yuqing Yang, Qipeng Guo, Xiangkun Hu +3
Recent works have introduced Abstract Meaning Representation (AMR) for Document-level Event Argument Extraction (Doc-level EAE), since AMR provides a useful interpretation of compl…
Exploiting Abstract Meaning Representation for Open-Domain Question Answering
Cunxiang Wang, Zhikun Xu, Qipeng Guo +4
The Open-Domain Question Answering (ODQA) task involves retrieving and subsequently generating answers from fine-grained relevant passages within a database. Current systems levera…
DORE: Document Ordered Relation Extraction based on Generative Framework
Qipeng Guo, Yuqing Yang, Hang Yan +2
In recent years, there is a surge of generation-based information extraction work, which allows a more direct use of pre-trained language models and efficiently captures output dep…
ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data Format
Qi Zhu, Christian Geishauser, Hsien-chin Lin +10
Task-oriented dialogue (TOD) systems function as digital assistants, guiding users through various tasks such as booking flights or finding restaurants. Existing toolkits for build…