3 citations · 4 across the 4 of their papers we have counts for
Showing cs.CLShow all
2 papers · 1 filter
cs.CL2026
Hierarchical Chain-of-Thought: Enhancing LLM Reasoning Performance and Efficiency
Xingshuai Huang, Derek Li, Bahareh Nikpour +1
Chain-of-Thought (CoT) prompting has significantly improved the reasoning capabilities of large language models (LLMs). However, conventional CoT often relies on unstructured, flat…
cs.CL2024★ 3 cited
Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models
Xindi Wang, Mahsa Salmani, Parsa Omidi +3
Recently, large language models (LLMs) have shown remarkable capabilities including understanding context, engaging in logical reasoning, and generating responses. However, this is…