7 papers · 1 filter
IFEval-Audio: Benchmarking Instruction-Following Capability in Audio-based Large Language Models
Yiming Gao, Bin Wang, Chengwei Wei +2
Large language models (LLMs) have demonstrated strong instruction-following capabilities in text-based tasks. However, this ability often deteriorates in multimodal models after al…
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…
Advancing Singlish Understanding: Bridging the Gap with Datasets and Multimodal Models
Bin Wang, Xunlong Zou, Shuo Sun +6
Singlish, a Creole language rooted in English, is a key focus in linguistic research within multilingual and multicultural contexts. However, its spoken form remains underexplored,…
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…
Word Embedding Dimension Reduction via Weakly-Supervised Feature Selection
Jintang Xue, Yun-Cheng Wang, Chengwei Wei +1
As a fundamental task in natural language processing, word embedding converts each word into a representation in a vector space. A challenge with word embedding is that as the voca…
Resilience of Large Language Models for Noisy Instructions
Bin Wang, Chengwei Wei, Zhengyuan Liu +2
As the rapidly advancing domain of natural language processing (NLP), large language models (LLMs) have emerged as powerful tools for interpreting human commands and generating tex…