activity
20202023
most citedTaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

9 citations · 21 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2023

Temporal Fact Reasoning over Hyper-Relational Knowledge Graphs

Zifeng Ding, Jingcheng Wu, Jingpei Wu +2

Stemming from traditional knowledge graphs (KGs), hyper-relational KGs (HKGs) provide additional key-value pairs (i.e., qualifiers) for each KG fact that help to better restrict th…

cs.CL2023

Assessing Phrase Break of ESL Speech with Pre-trained Language Models and Large Language Models

Zhiyi Wang, Shaoguang Mao, Wenshan Wu +3

This work introduces approaches to assessing phrase breaks in ESL learners' speech using pre-trained language models (PLMs) and large language models (LLMs). There are two tasks: o…

cs.CL2023

Smart Word Suggestions for Writing Assistance

Chenshuo Wang, Shaoguang Mao, Tao Ge +5

Enhancing word usage is a desired feature for writing assistance. To further advance research in this area, this paper introduces "Smart Word Suggestions" (SWS) task and benchmark.…

cs.CL2023★ 9 cited

Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting

Haoyang Huang, Tianyi Tang, Dongdong Zhang +4

Large language models (LLMs) demonstrate impressive multilingual capability, but their performance varies substantially across different languages. In this work, we introduce a sim…

cs.AI2023★ 9 cited

TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

Yaobo Liang, Chenfei Wu, Ting Song +11

Artificial Intelligence (AI) has made incredible progress recently. On the one hand, advanced foundation models like ChatGPT can offer powerful conversation, in-context learning an…

cs.CL2022

Assessing Phrase Break of ESL speech with Pre-trained Language Models

Zhiyi Wang, Shaoguang Mao, Wenshan Wu +1

This work introduces an approach to assessing phrase break in ESL learners' speech with pre-trained language models (PLMs). Different with traditional methods, this proposal conver…

cs.CL2021★ 2 cited

An Approach to Mispronunciation Detection and Diagnosis with Acoustic, Phonetic and Linguistic (APL) Embeddings

Wenxuan Ye, Shaoguang Mao, Frank Soong +4

Many mispronunciation detection and diagnosis (MD&D) research approaches try to exploit both the acoustic and linguistic features as input. Yet the improvement of the performance i…

eess.AS2020★ 1 cited

Improving pronunciation assessment via ordinal regression with anchored reference samples

Bin Su, Shaoguang Mao, Frank Soong +3

Sentence level pronunciation assessment is important for Computer Assisted Language Learning (CALL). Traditional speech pronunciation assessment, based on the Goodness of Pronuncia…