5 papers
Min- Sampling: Decoupling Truncation from Temperature Scaling via Relative Logit Dynamics
Yuanhao Ding, Meimingwei Li, Esteban Garces Arias +3
The quality of text generated by large language models depends critically on the decoding sampling strategy. While mainstream methods such as Top-, Top-, and Min- achieve…
GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation
Yuanhao Ding, Esteban Garces Arias, Meimingwei Li +6
Open-ended text generation faces a critical challenge: balancing coherence with diversity in LLM outputs. While contrastive search-based decoding strategies have emerged to address…
Unveiling Factors for Enhanced POS Tagging: A Study of Low-Resource Medieval Romance Languages
Matthias Schöffel, Esteban Garces Arias, Marinus Wiedner +4
Part-of-speech (POS) tagging remains a foundational component in natural language processing pipelines, particularly critical for historical text analysis at the intersection of co…
Towards Better Open-Ended Text Generation: A Multicriteria Evaluation Framework
Esteban Garces Arias, Hannah Blocher, Julian Rodemann +3
Open-ended text generation has become a prominent task in natural language processing due to the rise of powerful (large) language models. However, evaluating the quality of these…
Decoding Decoded: Understanding Hyperparameter Effects in Open-Ended Text Generation
Esteban Garces Arias, Meimingwei Li, Christian Heumann +1
Decoding strategies for generative large language models (LLMs) are a critical but often underexplored aspect of text generation tasks. Guided by specific hyperparameters, these st…