40 citations · 63 across the 5 of their papers we have counts for
5 papers
When Is Rank-1 Enough? Geometry-Guided Initialization for Parameter-Efficient Fine-Tuning
Haoran Zhao, Soyeon Caren Han, Eduard Hovy
Parameter-efficient fine-tuning (PEFT) is a standard way to adapt multimodal large language models, yet extremely low-rank settings -- especially rank-1 LoRA -- are often unstable.…
Non-literal Understanding of Number Words by Language Models
Polina Tsvilodub, Kanishk Gandhi, Haoran Zhao +3
Humans naturally interpret numbers non-literally, effortlessly combining context, world knowledge, and speaker intent. We investigate whether large language models (LLMs) interpret…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1168
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
LawLLM: Law Large Language Model for the US Legal System
Dong Shu, Haoran Zhao, Xukun Liu +3
In the rapidly evolving field of legal analytics, finding relevant cases and accurately predicting judicial outcomes are challenging because of the complexity of legal language, wh…
Materials Science Ontology Design with an Analytico-Synthetic Facet Analysis Framework
Jane Greenberg, Scott McClellan, Xintong Zhao +6
Researchers across nearly every discipline seek to leverage ontologies for knowledge discovery and computational tasks; yet, the number of machine readable materials science ontolo…