112 citations · 340 across the 21 of their papers we have counts for
9 papers · 1 filter
Can LLMs Reason Abstractly Over Math Word Problems Without CoT? Disentangling Abstract Formulation From Arithmetic Computation
Ziling Cheng, Meng Cao, Leila Pishdad +2
Final-answer-based metrics are commonly used for evaluating large language models (LLMs) on math word problems, often taken as proxies for reasoning ability. However, such metrics…
An Equal-Size Hard EM Algorithm for Diverse Dialogue Generation
Yuqiao Wen, Yongchang Hao, Yanshuai Cao +1
Open-domain dialogue systems aim to interact with humans through natural language texts in an open-ended fashion. Despite the recent success of super large dialogue systems such as…
Hierarchical Neural Data Synthesis for Semantic Parsing
Wei Yang, Peng Xu, Yanshuai Cao
Semantic parsing datasets are expensive to collect. Moreover, even the questions pertinent to a given domain, which are the input of a semantic parsing system, might not be readily…
Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface
Peng Xu, Wenjie Zi, Hamidreza Shahidi +7
A natural language database interface (NLDB) can democratize data-driven insights for non-technical users. However, existing Text-to-SQL semantic parsers cannot achieve high enough…
A Globally Normalized Neural Model for Semantic Parsing
Chenyang Huang, Wei Yang, Yanshuai Cao +2
In this paper, we propose a globally normalized model for context-free grammar (CFG)-based semantic parsing. Instead of predicting a probability, our model predicts a real-valued s…
Optimizing Deeper Transformers on Small Datasets
Peng Xu, Dhruv Kumar, Wei Yang +6
It is a common belief that training deep transformers from scratch requires large datasets. Consequently, for small datasets, people usually use shallow and simple additional layer…
On Variational Learning of Controllable Representations for Text without Supervision
Peng Xu, Jackie Chi Kit Cheung, Yanshuai Cao
The variational autoencoder (VAE) can learn the manifold of natural images on certain datasets, as evidenced by meaningful interpolating or extrapolating in the continuous latent s…
A Cross-Domain Transferable Neural Coherence Model
Peng Xu, Hamidreza Saghir, Jin Sung Kang +4
Coherence is an important aspect of text quality and is crucial for ensuring its readability. One important limitation of existing coherence models is that training on one domain d…
Adversarial Contrastive Estimation
Avishek Joey Bose, Huan Ling, Yanshuai Cao
Learning by contrasting positive and negative samples is a general strategy adopted by many methods. Noise contrastive estimation (NCE) for word embeddings and translating embeddin…