16 citations · 16 across the 2 of their papers we have counts for
2 papers
cs.CL2026
CLaS-Bench: A Cross-Lingual Alignment and Steering Benchmark
Daniil Gurgurov, Yusser Al Ghussin, Tanja Baeumel +5
Understanding and controlling the behavior of large language models (LLMs) is an increasingly important topic in multilingual NLP. Beyond prompting or fine-tuning, , i.e.,~manipula…
cs.CL2022★ 16 cited
Measuring Causal Effects of Data Statistics on Language Model's `Factual' Predictions
Yanai Elazar, Nora Kassner, Shauli Ravfogel +6
Large amounts of training data are one of the major reasons for the high performance of state-of-the-art NLP models. But what exactly in the training data causes a model to make a…