20 citations · 28 across the 8 of their papers we have counts for
6 papers · 1 filter
Towards Spoken Mathematical Reasoning: Benchmarking Speech-based Models over Multi-faceted Math Problems
Chengwei Wei, Bin Wang, Jung-jae Kim +1
Recent advances in large language models (LLMs) and multimodal LLMs (MLLMs) have led to strong reasoning ability across a wide range of tasks. However, their ability to perform mat…
CoinMath: Harnessing the Power of Coding Instruction for Math LLMs
Chengwei Wei, Bin Wang, Jung-jae Kim +2
Large Language Models (LLMs) have shown strong performance in solving mathematical problems, with code-based solutions proving particularly effective. However, the best practice to…
Shall We Trust All Relational Tuples by Open Information Extraction? A Study on Speculation Detection
Kuicai Dong, Aixin Sun, Jung-Jae Kim +1
Open Information Extraction (OIE) aims to extract factual relational tuples from open-domain sentences. Downstream tasks use the extracted OIE tuples as facts, without examining th…
Open Information Extraction via Chunks
Kuicai Dong, Aixin Sun, Jung-Jae Kim +1
Open Information Extraction (OIE) aims to extract relational tuples from open-domain sentences. Existing OIE systems split a sentence into tokens and recognize token spans as tuple…
Syntactic Multi-view Learning for Open Information Extraction
Kuicai Dong, Aixin Sun, Jung-Jae Kim +1
Open Information Extraction (OpenIE) aims to extract relational tuples from open-domain sentences. Traditional rule-based or statistical models have been developed based on syntact…
DocOIE: A Document-level Context-Aware Dataset for OpenIE
Kuicai Dong, Yilin Zhao, Aixin Sun +2
Open Information Extraction (OpenIE) aims to extract structured relational tuples (subject, relation, object) from sentences and plays critical roles for many downstream NLP applic…