21 citations · 63 across the 37 of their papers we have counts for
6 papers · 2 filters
Stochastic Estimation of Transduced Language Models
Vésteinn Snæbjarnarson, Samuel Kiegeland, Manuel de Prada Corral +2
Transduced language models (TLMs) compose a pretrained \emph{source} language model with a functional finite-state transducer to induce a language model over \emph{target} strings.…
On the Proper Treatment of Units in Surprisal Theory
Samuel Kiegeland, Vésteinn Snæbjarnarson, Tim Vieira +1
Surprisal theory links human processing effort to the predictability of an upcoming linguistic unit, but empirical work often leaves the notion of a unit underspecified. In practic…
Prefix Parsing is Just Parsing
Clemente Pasti, Andreas Opedal, Timothy J. O'Donnell +2
Prefix parsing asks whether an input prefix can be extended to a complete string generated by a given grammar. In the weighted setting, it also provides prefix probabilities, which…
Ensembling Language Models with Sequential Monte Carlo
Robin Shing Moon Chan, Tianyu Liu, Samuel Kiegeland +5
Practitioners have access to an abundance of language models and prompting strategies for solving many language modeling tasks; yet prior work shows that modeling performance is hi…
Transducing Language Models
Vésteinn Snæbjarnarson, Samuel Kiegeland, Tianyu Liu +3
Modern language models define distributions over strings, but downstream tasks often require different output formats. For instance, a model that generates byte-pair strings does n…
Post-Training Language Models for Crosslingual Consistency
Tianyu Liu, Jirui Qi, Mrinmaya Sachan +3
Language models often respond inconsistently to translation-equivalent prompts across languages, undermining the reliability of multilingual systems. To quantify this, we give an i…