3 citations · 3 across the 5 of their papers we have counts for
5 papers
MIDR: Enrichment-Augmented Indexing for Multimodal Document Retrieval
Debanjan Mahata, Atharva Tendle, Daniel Preotiuc-Pietro +2
Retrieval over visually rich documents has a representation problem: important content often lives in tables, charts, figures, and layout relations that plain OCR linearizes, corru…
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…
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…
Improving Instruct Models for Free: A Study on Partial Adaptation
Ozan İrsoy, 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…