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cs.AI2026
From Atoms to Trees: Building a Structured Feature Forest with Hierarchical Sparse Autoencoders
Yifan Luo, Yang Zhan, Jiedong Jiang +4
Sparse autoencoders (SAEs) have proven effective for extracting monosemantic features from large language models (LLMs), yet these features are typically identified in isolation. H…
cs.AI2024
Demonstration Notebook: Finding the Most Suited In-Context Learning Example from Interactions
Yiming Tang, Bin Dong
Large language models (LLMs) benefit greatly from prompt engineering, with in-context learning standing as a pivital technique. While former approaches have provided various ways t…