Injecting Hierarchy with U-Net Transformers. - David Donahue; Vladislav Lialin; Anna Rumshisky (CoRR, 2019)

Continual Learning for Neural Semantic Parsing. - Vladislav Lialin; Rahul Goel; Andrey Simanovsky; Anna Rumshisky; Rushin Shah (CoRR, 2020)

Life after BERT: What do Other Muppets Understand about Language? - Vladislav Lialin; Kevin Zhao; Namrata Shivagunde; Anna Rumshisky (ACL (1), 2022)

Learning to Ask Like a Physician. - Eric Lehman; Vladislav Lialin; Katelyn Y. Legaspi; Anne Janelle R. Sy; Patricia Therese S. Pile; Nicole Rose I. Alberto; Richard Raymund R. Ragasa; Corinna Victoria M. Puyat; Isabelle Rose I. Alberto; Pia Gabrielle I. Alfonso; Marianne Taliño; Dana Moukheiber; et al. (CoRR, 2022)

Honey, I Shrunk the Language: Language Model Behavior at Reduced Scale. - Vijeta Deshpande; Dan Pechi; Shree Thatte; Vladislav Lialin; Anna Rumshisky (ACL (Findings), 2023)

Larger Probes Tell a Different Story: Extending Psycholinguistic Datasets Via In-Context Learning. - Namrata Shivagunde; Vladislav Lialin; Anna Rumshisky (EMNLP, 2023)

Scalable and Accurate Self-supervised Multimodal Representation Learning without Aligned Video and Text Data. - Vladislav Lialin; Stephen Rawls; David Chan; Shalini Ghosh; Anna Rumshisky; Wael Hamza (WACV (Workshops), 2023)

Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning. - Vladislav Lialin; Vijeta Deshpande; Anna Rumshisky (CoRR, 2023)

Stack More Layers Differently: High-Rank Training Through Low-Rank Updates. - Vladislav Lialin; Namrata Shivagunde; Sherin Muckatira; Anna Rumshisky (CoRR, 2023)

Let's Reinforce Step by Step. - Sarah Pan; Vladislav Lialin; Sherin Muckatira; Anna Rumshisky (CoRR, 2023)

NarrativeTime: Dense Temporal Annotation on a Timeline. - Anna Rogers; Marzena Karpinska; Ankita Gupta; Vladislav Lialin; Gregory Smelkov; Anna Rumshisky (LREC/COLING, 2024)

Deconstructing In-Context Learning: Understanding Prompts via Corruption. - Namrata Shivagunde; Vladislav Lialin; Sherin Muckatira; Anna Rumshisky (LREC/COLING, 2024)

ReLoRA: High-Rank Training Through Low-Rank Updates. - Vladislav Lialin; Sherin Muckatira; Namrata Shivagunde; Anna Rumshisky (ICLR, 2024)

Emergent Abilities in Reduced-Scale Generative Language Models. - Sherin Muckatira; Vijeta Deshpande; Vladislav Lialin; Anna Rumshisky (NAACL-HLT (Findings), 2024)

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. - Hyewon Jeong; Sarah Jabbour; Yuzhe Yang 003; Rahul Thapa; Hussein Mozannar; William Jongwon Han; Nikita Mehandru; Michael Wornow; Vladislav Lialin; Xin Liu 034; Alejandro Lozano; Jiacheng Zhu; et al. (CoRR, 2024)