8 papers
Modeling semantic association in self-paced reading with language model embeddings
Sara Møller Ãstergaard, Kenneth Enevoldsen, Afra Alishahi +1
Semantic association between a word and its context has been identified as an important component of reading comprehension, even when word predictability is accounted for. Recent r…
Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe
Gaofei Shen, Martijn Bentum, Tom Lentz +2
Probing is widely used to study which features can be decoded from language model representations. However, the common decoding probe approach has two limitations that we aim to so…
In-Context Learning in Speech Language Models: Analyzing the Role of Acoustic Features, Linguistic Structure, and Induction Heads
Charlotte Pouw, Hosein Mohebbi, Afra Alishahi +1
In-Context Learning (ICL) has been extensively studied in text-only Language Models, but remains largely unexplored in the speech domain. Here, we investigate how linguistic and ac…
Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures
Chiara Manna, Hosein Mohebbi, Afra Alishahi +2
While Large Language Models achieve state-of-the-art results across a wide range of NLP tasks, they remain prone to systematic biases. Among these, gender bias is particularly sali…
A Linguistically Motivated Analysis of Intonational Phrasing in Text-to-Speech Systems: Revealing Gaps in Syntactic Sensitivity
Charlotte Pouw, Afra Alishahi, Willem Zuidema
We analyze the syntactic sensitivity of Text-to-Speech (TTS) systems using methods inspired by psycholinguistic research. Specifically, we focus on the generation of intonational p…
On the reliability of feature attribution methods for speech classification
Gaofei Shen, Hosein Mohebbi, Arianna Bisazza +2
As the capabilities of large-scale pre-trained models evolve, understanding the determinants of their outputs becomes more important. Feature attribution aims to reveal which parts…