5 papers
PolyFact: Comparing Consistency-Driven Post-training Methods for Cross-Lingual Factual Recall
Jonathan von Rad, Louis Arts, George Burgess +6
Large language models (LLMs) trained predominantly on English data encode substantial world knowledge, yet often fail to express it reliably in other languages, a phenomenon known…
DatedGPT: Preventing Lookahead Bias in Large Language Models with Time-Aware Pretraining
Yutong Yan, Raphael Tang, Zhenyu Gao +2
Large language models pretrained on internet-scale data risk lookahead bias in forecasting tasks, as they may have already seen the true outcome during training. To address this, w…
The Role of Mixed-Language Documents for Multilingual Large Language Model Pretraining
Jiandong Shao, Raphael Tang, Crystina Zhang +4
Multilingual large language models achieve impressive cross-lingual performance despite largely monolingual pretraining. While bilingual data in pretraining corpora is widely belie…
Words Worth a Thousand Pictures: Measuring and Understanding Perceptual Variability in Text-to-Image Generation
Raphael Tang, Xinyu Zhang, Lixinyu Xu +5
Diffusion models are the state of the art in text-to-image generation, but their perceptual variability remains understudied. In this paper, we examine how prompts affect image var…
AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages
Jiayi Wang, David Ifeoluwa Adelani, Sweta Agrawal +55
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measuring this progress remains challenging, s…