7 papers · 1 filter
Beg to Differ: Understanding Reasoning-Answer Misalignment Across Languages
Anaelia Ovalle, Candace Ross, Sebastian Ruder +4
Large language models demonstrate strong reasoning capabilities through chain-of-thought prompting, but whether this reasoning quality transfers across languages remains underexplo…
BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop
Lucas Charpentier, Leshem Choshen, Ryan Cotterell +11
BabyLM aims to dissolve the boundaries between cognitive modeling and language modeling. We call for both workshop papers and for researchers to join the 3rd BabyLM competition. As…
Improving Model Evaluation using SMART Filtering of Benchmark Datasets
Vipul Gupta, Candace Ross, David Pantoja +3
One of the most challenging problems facing NLP today is evaluation. Some of the most pressing issues pertain to benchmark saturation, data contamination, and diversity in the qual…
What makes a good metric? Evaluating automatic metrics for text-to-image consistency
Candace Ross, Melissa Hall, Adriana Romero Soriano +1
Language models are increasingly being incorporated as components in larger AI systems for various purposes, from prompt optimization to automatic evaluation. In this work, we anal…
Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora
Michael Y. Hu, Aaron Mueller, Candace Ross +7
The BabyLM Challenge is a community effort to close the data-efficiency gap between human and computational language learners. Participants compete to optimize language model train…
Changing Answer Order Can Decrease MMLU Accuracy
Vipul Gupta, David Pantoja, Candace Ross +2
As large language models (LLMs) have grown in prevalence, particular benchmarks have become essential for the evaluation of these models and for understanding model capabilities. M…