activity
20162023
most citedUsing millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

431 citations · 857 across the 69 of their papers we have counts for

collaborators
Showing 2023Show all

12 papers · 1 filter

cs.LG2023★ 2 cited

Large language models converge toward human-like concept organization

Mathias Lykke Gammelgaard, Jonathan Gabel Christiansen, Anders Søgaard

Large language models show human-like performance in knowledge extraction, reasoning and dialogue, but it remains controversial whether this performance is best explained by memori…

cs.CL2023★ 1 cited

Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models

Phillip Rust, Anders Søgaard

Language models such as mBERT, XLM-R, and BLOOM aim to achieve multilingual generalization or compression to facilitate transfer to a large number of (potentially unseen) languages…

cs.CL2023★ 4 cited

Mapping Brains with Language Models: A Survey

Antonia Karamolegkou, Mostafa Abdou, Anders Søgaard

Over the years, many researchers have seemingly made the same observation: Brain and language model activations exhibit some structural similarities, enabling linear partial mappin…

cs.CL2023★ 5 cited

Structural Similarities Between Language Models and Neural Response Measurements

Jiaang Li, Antonia Karamolegkou, Yova Kementchedjhieva +3

Large language models (LLMs) have complicated internal dynamics, but induce representations of words and phrases whose geometry we can study. Human language processing is also opaq…

cs.CL2023

Being Right for Whose Right Reasons?

Terne Sasha Thorn Jakobsen, Laura Cabello, Anders Søgaard

Explainability methods are used to benchmark the extent to which model predictions align with human rationales i.e., are 'right for the right reasons'. Previous work has failed to…

cs.CL2023

What does the Failure to Reason with "Respectively" in Zero/Few-Shot Settings Tell Us about Language Models?

Ruixiang Cui, Seolhwa Lee, Daniel Hershcovich +1

Humans can effortlessly understand the coordinate structure of sentences such as "Niels Bohr and Kurt Cobain were born in Copenhagen and Seattle, respectively". In the context of n…