Information-theoretic measures derived from autoregressive language models are widely used to characterize the expectations that shape human reading, but whether language-variety-specific training improves such psycholinguistic alignment remains unclear. This question is still open for Cantonese, where recent NLP evalu...
Ziqi Zhang, Emmanuele Chersoni, Mohammad Momenian· 0 citations
Prompt compression shortens LLM input to reduce inference cost, yet existing methods score token importance through LM forward passes. It remains questionable whether such nuanced, costly token selection is necessary. Compression requires identifying informative content, a problem that linguistic research has long addr...
By categorizing LSC models into generations defined by key components, this investigation suggests that performance breakthroughs have been largely driven by advances in semantic representations, transitioning from count-based models to recent transformer-based approaches.
Jing Chen, Emmanuele Chersoni, Dominik Schlechtweg et al.· Natural Language Processing· 0 citations
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