2 citations · 2 across the 4 of their papers we have counts for
17 papers
The Role of -gram Smoothing in the Age of Neural Networks
Luca Malagutti, Andrius Buinovskij, Anej Svete +3
For nearly three decades, language models derived from the -gram assumption held the state of the art on the task. The key to their success lay in the application of various smo…
Mutual Information Alleviates Hallucinations in Abstractive Summarization
Liam van der Poel, Ryan Cotterell, Clara Meister
Despite significant progress in the quality of language generated from abstractive summarization models, these models still exhibit the tendency to hallucinate, i.e., output conten…
Estimating the Entropy of Linguistic Distributions
Aryaman Arora, Clara Meister, Ryan Cotterell
Shannon entropy is often a quantity of interest to linguists studying the communicative capacity of human language. However, entropy must typically be estimated from observed data…
On the probability-quality paradox in language generation
Clara Meister, Gian Wiher, Tiago Pimentel +1
When generating natural language from neural probabilistic models, high probability does not always coincide with high quality: It has often been observed that mode-seeking decodin…
On Decoding Strategies for Neural Text Generators
Gian Wiher, Clara Meister, Ryan Cotterell
When generating text from probabilistic models, the chosen decoding strategy has a profound effect on the resulting text. Yet the properties elicited by various decoding strategies…
A surprisal--duration trade-off across and within the world's languages
Tiago Pimentel, Clara Meister, Elizabeth Salesky +3
While there exist scores of natural languages, each with its unique features and idiosyncrasies, they all share a unifying theme: enabling human communication. We may thus reasonab…