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cs.CL2026★ 1 cited
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…
cs.CL2025
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…
cs.CL2024
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…