15 citations · 19 across the 5 of their papers we have counts for
5 papers
DataDecide: How to Predict Best Pretraining Data with Small Experiments
Ian Magnusson, Nguyen Tai, Ben Bogin +10
Because large language models are expensive to pretrain on different datasets, using smaller-scale experiments to decide on data is crucial for reducing costs. Which benchmarks and…
MMTEB: Massive Multilingual Text Embedding Benchmark
Kenneth Enevoldsen, Isaac Chung, Imene Kerboua +83
Text embeddings are typically evaluated on a limited set of tasks, which are constrained by language, domain, and task diversity. To address these limitations and provide a more co…
Software Entity Recognition with Noise-Robust Learning
Tai Nguyen, Yifeng Di, Joohan Lee +2
Recognizing software entities such as library names from free-form text is essential to enable many software engineering (SE) technologies, such as traceability link recovery, auto…
Explanation-based Finetuning Makes Models More Robust to Spurious Cues
Josh Magnus Ludan, Yixuan Meng, Tai Nguyen +4
Large Language Models (LLMs) are so powerful that they sometimes learn correlations between labels and features that are irrelevant to the task, leading to poor generalization on o…
In-context Example Selection with Influences
Tai Nguyen, Eric Wong
In-context learning (ICL) is a powerful paradigm emerged from large language models (LLMs). Despite its promises, ICL performance is known to be highly sensitive to input examples.…