117 citations · 630 across the 39 of their papers we have counts for
21 papers · 1 filter
Re-Reading Improves Reasoning in Large Language Models
Xiaohan Xu, Chongyang Tao, Tao Shen +5
To enhance the reasoning capabilities of off-the-shelf Large Language Models (LLMs), we introduce a simple, yet general and effective prompting method, Re2, i.e., \textbf{Re}-\text…
Improving the Robustness of Summarization Systems with Dual Augmentation
Xiuying Chen, Guodong Long, Chongyang Tao +4
A robust summarization system should be able to capture the gist of the document, regardless of the specific word choices or noise in the input. In this work, we first explore the…
Synergistic Interplay between Search and Large Language Models for Information Retrieval
Jiazhan Feng, Chongyang Tao, Xiubo Geng +5
Information retrieval (IR) plays a crucial role in locating relevant resources from vast amounts of data, and its applications have evolved from traditional knowledge bases to mode…
Large Language Models are Strong Zero-Shot Retriever
Tao Shen, Guodong Long, Xiubo Geng +3
In this work, we propose a simple method that applies a large language model (LLM) to large-scale retrieval in zero-shot scenarios. Our method, the Language language model as Retri…
Unsupervised Knowledge Graph Construction and Event-centric Knowledge Infusion for Scientific NLI
Chenglin Wang, Yucheng Zhou, Guodong Long +2
With the advance of natural language inference (NLI), a rising demand for NLI is to handle scientific texts. Existing methods depend on pre-trained models (PTM) which lack domain-s…
ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification
Yucheng Zhou, Tao Shen, Xiubo Geng +2
Generating new events given context with correlated ones plays a crucial role in many event-centric reasoning tasks. Existing works either limit their scope to specific scenarios o…