12 citations · 15 across the 8 of their papers we have counts for
12 papers · 1 filter
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Zhihan Zhang, Tao Ge, Zhenwen Liang +5
Supervised fine-tuning enhances the problem-solving abilities of language models across various mathematical reasoning tasks. To maximize such benefits, existing research focuses o…
Describe-then-Reason: Improving Multimodal Mathematical Reasoning through Visual Comprehension Training
Mengzhao Jia, Zhihan Zhang, Wenhao Yu +2
Open-source multimodal large language models (MLLMs) excel in various tasks involving textual and visual inputs but still struggle with complex multimodal mathematical reasoning, l…
PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning
Zhihan Zhang, Dong-Ho Lee, Yuwei Fang +4
Instruction tuning has remarkably advanced large language models (LLMs) in understanding and responding to diverse human instructions. Despite the success in high-resource language…
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Zhihan Zhang, Shuohang Wang, Wenhao Yu +6
Large language models (LLMs) can perform a wide range of tasks by following natural language instructions, without the necessity of task-specific fine-tuning. Unfortunately, the pe…
Investigating Cross-Domain Behaviors of BERT in Review Understanding
Albert Lu, Meng Jiang
Review score prediction requires review text understanding, a critical real-world application of natural language processing. Due to dissimilar text domains in product reviews, a c…
Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions
Zhihan Zhang, Wenhao Yu, Zheng Ning +2
Contrast consistency, the ability of a model to make consistently correct predictions in the presence of perturbations, is an essential aspect in NLP. While studied in tasks such a…