5 citations · 13 across the 13 of their papers we have counts for
5 papers · 1 filter
Generative Calibration for In-context Learning
Zhongtao Jiang, Yuanzhe Zhang, Cao Liu +2
As one of the most exciting features of large language models (LLMs), in-context learning is a mixed blessing. While it allows users to fast-prototype a task solver with only a few…
MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Models
Yifan Wei, Yisong Su, Huanhuan Ma +5
Large language models (LLMs) have shown nearly saturated performance on many natural language processing (NLP) tasks. As a result, it is natural for people to believe that LLMs hav…
Interpreting Sentiment Composition with Latent Semantic Tree
Zhongtao Jiang, Yuanzhe Zhang, Cao Liu +3
As the key to sentiment analysis, sentiment composition considers the classification of a constituent via classifications of its contained sub-constituents and rules operated on th…
Unsupervised Text Style Transfer with Deep Generative Models
Zhongtao Jiang, Yuanzhe Zhang, Yiming Ju +1
We present a general framework for unsupervised text style transfer with deep generative models. The framework models each sentence-label pair in the non-parallel corpus as partial…
Multi-View Graph Representation Learning for Answering Hybrid Numerical Reasoning Question
Yifan Wei, Fangyu Lei, Yuanzhe Zhang +2
Hybrid question answering (HybridQA) over the financial report contains both textual and tabular data, and requires the model to select the appropriate evidence for the numerical r…