2 citations · 2 across the 4 of their papers we have counts for
4 papers
SAFE-Cascade: Cost-Adaptive Vision-Language Routing for Chart Question Answering
Ayush Dwivedi, Qixin Wang, Ashvi Soni +5
Vision-language models (VLMs) are powerful for chart question answering, but invoking a VLM for every query can be unnecessarily expensive when many questions are answerable from O…
Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care
Saurabh Kumar, Sourav Bansal, Neeraj Agrawal +1
Customer care is an essential pillar of the e-commerce shopping experience with companies spending millions of dollars each year, employing automation and human agents, across geog…
Enhancing Customer Service Chatbots with Context-Aware NLU through Selective Attention and Multi-task Learning
Subhadip Nandi, Neeraj Agrawal, Anshika Singh +1
Customer service chatbots are conversational systems aimed at addressing customer queries, often by directing them to automated workflows. A crucial aspect of this process is the c…
Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model
Subhadip Nandi, Neeraj Agrawal
Few-Shot Cross-Domain NER is the process of leveraging knowledge from data-rich source domains to perform entity recognition on data scarce target domains. Most previous state-of-t…