2 citations · 7 across the 24 of their papers we have counts for
5 papers · 1 filter
From Language Models over Tokens to Language Models over Characters
Tim Vieira, Ben LeBrun, Mario Giulianelli +5
Modern language models are internally -- and mathematically -- distributions over strings rather than strings, posing numerous challenges for programm…
On the Proper Treatment of Tokenization in Psycholinguistics
Mario Giulianelli, Luca Malagutti, Juan Luis Gastaldi +3
Language models are widely used in computational psycholinguistics to test theories that relate the negative log probability (the surprisal) of a region of interest (a substring of…
The Foundations of Tokenization: Statistical and Computational Concerns
Juan Luis Gastaldi, John Terilla, Luca Malagutti +3
Tokenization - the practice of converting strings of characters from an alphabet into sequences of tokens over a vocabulary - is a critical step in the NLP pipeline. The use of tok…
Variational Best-of-N Alignment
Afra Amini, Tim Vieira, Elliott Ash +1
Best-of-N (BoN) is a popular and effective algorithm for aligning language models to human preferences. The algorithm works as follows: at inference time, N samples are drawn from…
Direct Preference Optimization with an Offset
Afra Amini, Tim Vieira, Ryan Cotterell
Direct preference optimization (DPO) is a successful fine-tuning strategy for aligning large language models with human preferences without the need to train a reward model or empl…