14 citations · 33 across the 17 of their papers we have counts for
14 papers · 1 filter
Learning Robust Named Entity Recognizers From Noisy Data With Retrieval Augmentation
Chaoyi Ai, Yong Jiang, Shen Huang +2
Named entity recognition (NER) models often struggle with noisy inputs, such as those with spelling mistakes or errors generated by Optical Character Recognition processes, and lea…
Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers
Chao Lou, Zixia Jia, Zilong Zheng +1
Accommodating long sequences efficiently in autoregressive Transformers, especially within an extended context window, poses significant challenges due to the quadratic computation…
Layer-Condensed KV Cache for Efficient Inference of Large Language Models
Haoyi Wu, Kewei Tu
Huge memory consumption has been a major bottleneck for deploying high-throughput large language models in real-world applications. In addition to the large number of parameters, t…
Using Interpretation Methods for Model Enhancement
Zhuo Chen, Chengyue Jiang, Kewei Tu
In the age of neural natural language processing, there are plenty of works trying to derive interpretations of neural models. Intuitively, when gold rationales exist during traini…
Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset
Haoyi Wu, Wenyang Hui, Yezeng Chen +3
Mathematical understanding and reasoning are crucial tasks for assessing the capabilities of artificial intelligence (AI). However, existing benchmarks either require just a few st…
Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural Networks
Zhaohui Yan, Songlin Yang, Wei Liu +1
Entity and Relation Extraction (ERE) is an important task in information extraction. Recent marker-based pipeline models achieve state-of-the-art performance, but still suffer from…