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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

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Showing 2023Show all

5 papers · 1 filter

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…