Search Results for author: Hongguang Li

Found 7 papers, 5 papers with code

From Good to Great: Improving Math Reasoning with Tool-Augmented Interleaf Prompting

no code implementations18 Dec 2023 Nuo Chen, Hongguang Li, Baoyuan Wang, Jia Li

IMP-TIP follows the ``From Good to Great" concept, collecting multiple potential solutions from both LLMs and their Tool-Augmented counterparts for the same math problem, and then selecting or re-generating the most accurate answer after cross-checking these solutions via tool-augmented interleaf prompting.

Diversity GSM8K +2

Take an Irregular Route: Enhance the Decoder of Time-Series Forecasting Transformer

1 code implementation10 Dec 2023 Li Shen, Yuning Wei, Yangzhu Wang, Hongguang Li

With the development of Internet of Things (IoT) systems, precise long-term forecasting method is requisite for decision makers to evaluate current statuses and formulate future policies.

Decoder Time Series +1

Natural Response Generation for Chinese Reading Comprehension

1 code implementation17 Feb 2023 Nuo Chen, Hongguang Li, Yinan Bao, Baoyuan Wang, Jia Li

To this end, we construct a new dataset called Penguin to promote the research of MRC, providing a training and test bed for natural response generation to real scenarios.

Chinese Reading Comprehension Machine Reading Comprehension +1

A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos

no code implementations8 Dec 2021 Xianlin Zeng, Yalong Jiang, Wenrui Ding, Hongguang Li, Yafeng Hao, Zifeng Qiu

High-level graph representations encode the trajectories of people and the interactions among multiple identities while low-level graph representations encode the local body postures of each person.

Anomaly Detection In Surveillance Videos

Robustness Testing of Language Understanding in Task-Oriented Dialog

2 code implementations ACL 2021 Jiexi Liu, Ryuichi Takanobu, Jiaxin Wen, Dazhen Wan, Hongguang Li, Weiran Nie, Cheng Li, Wei Peng, Minlie Huang

Most language understanding models in task-oriented dialog systems are trained on a small amount of annotated training data, and evaluated in a small set from the same distribution.

Data Augmentation Natural Language Understanding

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