1 citations · 4 across the 8 of their papers we have counts for
6 papers · 1 filter
MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling
MiniCPM Team, Wenhao An, Yingfa Chen +44
The evolution of large language models (LLMs) towards applications with ultra-long contexts faces challenges posed by the high computational and memory costs of the Transformer arc…
Lost in the Passage: Passage-level In-context Learning Does Not Necessarily Need a "Passage"
Hao Sun, Chenming Tang, Gengyang Li +1
By simply incorporating demonstrations into the context, in-context learning (ICL) enables large language models (LLMs) to yield awesome performance on many tasks. In this study, w…
Legal Evalutions and Challenges of Large Language Models
Jiaqi Wang, Huan Zhao, Zhenyuan Yang +19
In this paper, we review legal testing methods based on Large Language Models (LLMs), using the OPENAI o1 model as a case study to evaluate the performance of large models in apply…
Assessing the Performance of Chinese Open Source Large Language Models in Information Extraction Tasks
Yida Cai, Hao Sun, Hsiu-Yuan Huang +1
Information Extraction (IE) plays a crucial role in Natural Language Processing (NLP) by extracting structured information from unstructured text, thereby facilitating seamless int…
Unsupervised Distractor Generation via Large Language Model Distilling and Counterfactual Contrastive Decoding
Fanyi Qu, Hao Sun, Yunfang Wu
Within the context of reading comprehension, the task of Distractor Generation (DG) aims to generate several incorrect options to confuse readers. Traditional supervised methods fo…
Character-level Chinese Backpack Language Models
Hao Sun, John Hewitt
The Backpack is a Transformer alternative shown to improve interpretability in English language modeling by decomposing predictions into a weighted sum of token sense components. H…