2 citations · 3 across the 2 of their papers we have counts for
5 papers
CRAG -- Comprehensive RAG Benchmark
Xiao Yang, Kai Sun, Hao Xin +24
Retrieval-Augmented Generation (RAG) has recently emerged as a promising solution to alleviate Large Language Model (LLM)'s deficiency in lack of knowledge. Existing RAG datasets,…
Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?
Kai Sun, Yifan Ethan Xu, Hanwen Zha +2
Since the recent prosperity of Large Language Models (LLMs), there have been interleaved discussions regarding how to reduce hallucinations from LLM responses, how to increase the…
Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite
Xiao Yang, Ahmed K. Mohamed, Shashank Jain +6
Label error is a ubiquitous problem in annotated data. Large amounts of label error substantially degrades the quality of deep learning models. Existing methods to tackle the label…
Logic2Text: High-Fidelity Natural Language Generation from Logical Forms
Zhiyu Chen, Wenhu Chen, Hanwen Zha +4
Previous works on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences. However, for complex structured d…
Global Textual Relation Embedding for Relational Understanding
Zhiyu Chen, Hanwen Zha, Honglei Liu +3
Pre-trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream NLP tasks. In this work, we investigate how to…