no code implementations • 28 Feb 2024 • Craig W. Schmidt, Varshini Reddy, Haoran Zhang, Alec Alameddine, Omri Uzan, Yuval Pinter, Chris Tanner
Tokenization is a foundational step in Natural Language Processing (NLP) tasks, bridging raw text and language models.
no code implementations • 12 Jan 2024 • Varshini Reddy, Rik Koncel-Kedziorski, Viet Dac Lai, Michael Krumdick, Charles Lovering, Chris Tanner
For large language models (LLMs) to be effective in the financial domain -- where each decision can have a significant impact -- it is necessary to investigate realistic tasks and data.
no code implementations • 11 Nov 2023 • Rik Koncel-Kedziorski, Michael Krumdick, Viet Lai, Varshini Reddy, Charles Lovering, Chris Tanner
We demonstrate that the current bottleneck in performance is due to LLMs' limited business and financial understanding, highlighting the value of a challenging benchmark for quantitative reasoning within this domain.
1 code implementation • 8 Feb 2023 • Van Anh Le, Varshini Reddy, Zixi Chen, Mengyuan Li, Xinran Tang, Anthony Ortiz, Simone Fobi Nsutezo, Caleb Robinson
In this paper we propose a mask-conditional synthetic image generation model for creating synthetic satellite imagery datasets.
no code implementations • 2 Aug 2022 • Mark Penrod, Harrison Termotto, Varshini Reddy, Jiayu Yao, Finale Doshi-Velez, Weiwei Pan
For responsible decision making in safety-critical settings, machine learning models must effectively detect and process edge-case data.