1 code implementation • ACL 2022 • Rongzhi Zhang, Yue Yu, Pranav Shetty, Le Song, Chao Zhang
Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set is tedious and difficult.
1 code implementation • 29 Feb 2024 • Pranav Shetty, Aishat Adeboye, Sonakshi Gupta, Chao Zhang, Rampi Ramprasad
We present a natural language processing pipeline that was used to extract polymer solar cell property data from the literature and simulate various active learning strategies.
1 code implementation • 13 Nov 2023 • Jerry Junyang Cheung, Yuchen Zhuang, Yinghao Li, Pranav Shetty, Wantian Zhao, Sanjeev Grampurohit, Rampi Ramprasad, Chao Zhang
Scientific information extraction (SciIE), which aims to automatically extract information from scientific literature, is becoming more important than ever.
no code implementations • 4 Oct 2022 • Sushant Lenka, Pratyush Kerhalkar, Pranav Shetty, Harsh Gupta, Bhavam Vidyarthi, Ujjwal Verma
This work proposes two approaches for identifying flooded regions in UAV aerial images.
1 code implementation • 27 Sep 2022 • Pranav Shetty, Arunkumar Chitteth Rajan, Christopher Kuenneth, Sonkakshi Gupta, Lakshmi Prerana Panchumarti, Lauren Holm, Chao Zhang, Rampi Ramprasad
The ever-increasing number of materials science articles makes it hard to infer chemistry-structure-property relations from published literature.
1 code implementation • 18 Mar 2022 • Rongzhi Zhang, Yue Yu, Pranav Shetty, Le Song, Chao Zhang
Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set is tedious and difficult.
2 code implementations • ACL 2021 • Yinghao Li, Pranav Shetty, Lucas Liu, Chao Zhang, Le Song
To address this challenge, we propose a conditional hidden Markov model (CHMM), which can effectively infer true labels from multi-source noisy labels in an unsupervised way.