38 citations · 47 across the 5 of their papers we have counts for
5 papers
Let's Reinforce Step by Step
Sarah Pan, Vladislav Lialin, Sherin Muckatira +1
While recent advances have boosted LM proficiency in linguistic benchmarks, LMs consistently struggle to reason correctly on complex tasks like mathematics. We turn to Reinforcemen…
Honey, I Shrunk the Language: Language Model Behavior at Reduced Scale
Vijeta Deshpande, Dan Pechi, Shree Thatte +2
In recent years, language models have drastically grown in size, and the abilities of these models have been shown to improve with scale. The majority of recent scaling laws studie…
Scalable and Accurate Self-supervised Multimodal Representation Learning without Aligned Video and Text Data
Vladislav Lialin, Stephen Rawls, David Chan +3
Scaling up weakly-supervised datasets has shown to be highly effective in the image-text domain and has contributed to most of the recent state-of-the-art computer vision and multi…
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model
Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald +13
In this work, we demonstrate that multilingual large-scale sequence-to-sequence (seq2seq) models, pre-trained on a mixture of denoising and Causal Language Modeling (CLM) tasks, ar…
Evaluating Creative Language Generation: The Case of Rap Lyric Ghostwriting
Peter Potash, Alexey Romanov, Anna Rumshisky
Language generation tasks that seek to mimic human ability to use language creatively are difficult to evaluate, since one must consider creativity, style, and other non-trivial as…