HOLO: A Plugin to Exploit LLMs' Holographic Generation for Efficient Short-text Generation

A recent study published on arXiv (2601.22546) presents the 'Holographic Characteristic' of Large Language Models (LLMs), highlighting their inclination to identify target-side keywords early in the generation process. The researchers have introduced a plugin named HOLO, designed to utilize this characteristic to extract keywords within a constrained number of generation steps, subsequently finishing the sentence with parallel lexical constraints to enhance inference efficiency. This research fills a gap in understanding the specific features of LLMs' generative capabilities, particularly in relation to in-context learning and chain-of-thought skills. The paper is released as a replace-cross version and can be accessed on arXiv.