15 citations · 22 across the 20 of their papers we have counts for
11 papers · 1 filter
Multilingual GSM-Symbolic: What determines capability transfer across languages?
Kenneth Enevoldsen, Riley Herchert, Sofie Mosegaard +22
We understand little about how capabilities acquired in one language carry over to another, or what governs this transfer: evaluations rely on incomparable, saturation-prone datase…
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
Mimir: A Sub-2B Hierarchical Reasoning Model Trained on Permissible Data Punches Above Its Weight Class
Peter Schneider-Kamp, Jacob Nielsen, Gianluca Barmina +4
Training capable language models typically relies on web-scale pretraining followed by multi-stage post-training, creating substantial computational and data-governance barriers fo…
MVEB: Massive Video Embedding Benchmark
Adnan El Assadi, Roman Solomatin, Isaac Chung +13
We introduce the Massive Video Embedding Benchmark (MVEB), a 23-task benchmark for video embeddings spanning classification, zero-shot classification, clustering, pair classificati…
Modeling semantic association in self-paced reading with language model embeddings
Sara Møller Østergaard, 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…
Grounding Text Embeddings in Stakeholder Associations
Jonathan Rystrøm, Sofie Burgos-Thorsen, Zihao Fu +3
Text embeddings are widely used to analyse large corpora of complex texts. However, it is unclear whether the embeddings capture the same semantic distances as the human experts us…
Naturalistic measure of social norms alignment
Yevhen Kostiuk, Kenneth Enevoldsen, Peter Bjerregaard Vahlstrup +2
Social norms reflect shared expectations on acceptable behavior. Measuring social norms alignment remains challenging, with existing approaches typically relying on artificial clos…
Closed-form predictive coding via hierarchical Gaussian filters
Aleksandrs Baskakovs, Sylvain Estebe, Kenneth Enevoldsen +3
Predictive coding (PC) offers a local and biologically grounded alternative to backpropagation in the training of artificial neural networks, yet to date, it remains slower, and pe…
One prompt is not enough: Instruction Sensitivity Undermines Embedding Model Evaluation
Yevhen Kostiuk, Kenneth Enevoldsen
Instruction embedding models have become common among state-of-the-art models, however are evaluated using a single prompt per task. The single-point evaluation ignores a main prob…
Improving reasoning at inference time via uncertainty minimisation
Nicolas Legrand, Kenneth Enevoldsen, Márton Kardos +1
Large language models (LLMs) now exhibit strong multi-step reasoning abilities, but existing inference-time scaling methods remain computationally expensive, often relying on exten…
MAEB: Massive Audio Embedding Benchmark
Adnan El Assadi, Isaac Chung, Chenghao Xiao +15
We introduce the Massive Audio Embedding Benchmark (MAEB), a large-scale benchmark covering 30 tasks across speech, music, environmental sounds, and cross-modal audio-text reasonin…