4 papers
Improving Instruct Models for Free: A Study on Partial Adaptation
Ozan Ä°rsoy, Pengxiang Cheng, Jennifer L. Chen +3
Instruct models, obtained from various instruction tuning or post-training steps, are commonly deemed superior and more usable than their base counterpart. While the model gains in…
Calibrating LLMs for Text-to-SQL Parsing by Leveraging Sub-clause Frequencies
Terrance Liu, Shuyi Wang, Daniel Preotiuc-Pietro +2
While large language models (LLMs) achieve strong performance on text-to-SQL parsing, they sometimes exhibit unexpected failures in which they are confidently incorrect. Building t…
Modeling and Detecting Company Risks from News: A Case Study in Bloomberg News
Jiaxin Pei, Soumya Vadlamannati, Liang-Kang Huang +2
Identifying risks associated with a company is important to investors and the well-being of the overall financial market. In this study, we build a computational framework to autom…
An Alternative to FLOPS Regularization to Effectively Productionize SPLADE-Doc
Aldo Porco, Dhruv Mehra, Igor Malioutov +5
Learned Sparse Retrieval (LSR) models encode text as weighted term vectors, which need to be sparse to leverage inverted index structures during retrieval. SPLADE, the most popular…