1 code implementation • 24 Oct 2023 • Rajdeep Mukherjee, Nithish Kannen, Saurabh Kumar Pandey, Pawan Goyal
We then (pre)train an encoder-decoder model by applying contrastive learning on the decoder-generated aspect-aware sentiment representations of the masked terms.
Ranked #2 on Aspect Sentiment Triplet Extraction on ASTE-Data-V2
Aspect Sentiment Triplet Extraction Aspect Term Extraction and Sentiment Classification +3
no code implementations • 21 Mar 2022 • Nithish Kannen, Udit Sharma, Sumit Neelam, Dinesh Khandelwal, Shajith Ikbal, Hima Karanam, L Venkata Subramaniam
This allows us to spot those facts that failed to get retrieved from the KB and generate textual queries to extract them from the textual resources in an open-domain question answering fashion.
Knowledge Base Question Answering Open-Domain Question Answering +1
1 code implementation • 25 Dec 2021 • Nithish Kannen, Divyanshu Sheth, Abhranil Chandra, Shubhraneel Pal
Acronyms and long-forms are commonly found in research documents, more so in documents from scientific and legal domains.