Stop: A Dataset for Spoken Task Oriented Semantic Parsing. - Paden Tomasello; Akshat Shrivastava; Daniel Lazar; Po-Chun Hsu; Duc Le; Adithya Sagar; Ali Elkahky; Jade Copet; Wei-Ning Hsu; Yossi Adi; Robin Algayres; Tu Anh Nguyen; et al. (SLT, 2022)

STOP: A dataset for Spoken Task Oriented Semantic Parsing. - Paden Tomasello; Akshat Shrivastava; Daniel Lazar; Po-Chun Hsu; Duc Le; Adithya Sagar; Ali Elkahky; Jade Copet; Wei-Ning Hsu; Yossef Mordechay; Robin Algayres; Tu Anh Nguyen; et al. (CoRR, 2022)

ICASSP 2023 Spoken Language Understanding Grand Challenge. - Akshat Shrivastava; Suyoun Kim; Paden Tomasello; Ali Elkahky; Daniel Lazar; Trang Le; Shan Jiang; Duc Le; Aleksandr Livshits; Ahmed Aly (ICASSP, 2023)

Privately Customizing Prefinetuning to Better Match User Data in Federated Learning. - Charlie Hou; Hongyuan Zhan; Akshat Shrivastava; Sid Wang; Aleksandr Livshits; Giulia Fanti; Daniel Lazar (CoRR, 2023)

Augmenting text for spoken language understanding with Large Language Models. - Roshan Sharma; Suyoun Kim; Daniel Lazar; Trang Le; Akshat Shrivastava; Kwanghoon Ahn; Piyush Kansal; Leda Sari; Ozlem Kalinli; Michael L. Seltzer (CoRR, 2023)

PRoDeliberation: Parallel Robust Deliberation for End-to-End Spoken Language Understanding. - Trang Le; Daniel Lazar; Suyoun Kim; Shan Jiang; Duc Le; Adithya Sagar; Aleksandr Livshits; Ahmed Aly; Akshat Shrivastava (EMNLP (Findings), 2024)

PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs. - Charlie Hou; Akshat Shrivastava; Hongyuan Zhan; Rylan Conway; Trang Le; Adithya Sagar; Giulia Fanti; Daniel Lazar (ICML, 2024)

Private Federated Learning using Preference-Optimized Synthetic Data. - Charlie Hou; Mei-Yu Wang; Yige Zhu; Daniel Lazar; Giulia Fanti (CoRR, 2025)