9 papers
What is the Best Sequence Length for BABYLM?
Suchir Salhan, Richard Diehl Martinez, Zébulon Goriely +1
Transformer language models typically operate with a fixed-length context window, which has grown in step with large-scale pretraining datasets. In the BabyLM Challenge, however, m…
BLiSS 1.0: Evaluating Bilingual Learner Competence in Second Language Small Language Models
Yuan Gao, Suchir Salhan, Andrew Caines +2
To bridge the gap between performance-oriented benchmarks and the evaluation of cognitively inspired models, we introduce BLiSS 1.0, a Benchmark of Learner Interlingual Syntactic S…
Meta-Pretraining for Zero-Shot Cross-Lingual Named Entity Recognition in Low-Resource Philippine Languages
David Demitri Africa, Suchir Salhan, Yuval Weiss +2
Named-entity recognition (NER) in low-resource languages is usually tackled by finetuning very large multilingual LMs, an option that is often infeasible in memory- or latency-cons…
Investigating ReLoRA: Effects on the Learning Dynamics of Small Language Models
Yuval Weiss, David Demitri Africa, Paula Buttery +1
Parameter-efficient methods like LoRA have revolutionised large language model (LLM) fine-tuning. ReLoRA extends this idea to pretraining by repeatedly merging and reinitialising l…
Pico: A Modular Framework for Hypothesis-Driven Small Language Model Research
Richard Diehl Martinez, David Demitri Africa, Yuval Weiss +3
Building language models (LMs), especially small and medium ones, remains more art than science. While large LMs often improve by sheer scale, it is still unclear why many design c…
Learning Dynamics of Meta-Learning in Small Model Pretraining
David Demitri Africa, Yuval Weiss, Paula Buttery +1
Large language models are powerful but costly. We ask whether meta-learning can make the pretraining of small language models not only better but also more interpretable. We integr…