6 papers
MoEMoE: Question Guided Dense and Scalable Sparse Mixture-of-Expert for Multi-source Multi-modal Answering
Vinay Kumar Verma, Shreyas Sunil Kulkarni, Happy Mittal +1
Question Answering (QA) and Visual Question Answering (VQA) are well-studied problems in the language and vision domain. One challenging scenario involves multiple sources of infor…
Large Scale Generative Multimodal Attribute Extraction for E-commerce Attributes
Anant Khandelwal, Happy Mittal, Shreyas Sunil Kulkarni +1
E-commerce websites (e.g. Amazon) have a plethora of structured and unstructured information (text and images) present on the product pages. Sellers often either don't label or mis…
Distantly Supervised Transformers For E-Commerce Product QA
Happy Mittal, Aniket Chakrabarti, Belhassen Bayar +2
We propose a practical instant question answering (QA) system on product pages of ecommerce services, where for each user query, relevant community question answer (CQA) pairs are…
Advances in Symmetry Breaking for SAT Modulo Theories
Saket Dingliwal, Ronak Agarwal, Happy Mittal +1
Symmetry breaking is a popular technique to reduce the search space for SAT solving by exploiting the underlying symmetry over variables and clauses in a formula. The key idea is t…
Lifted Marginal MAP Inference
Vishal Sharma, Noman Ahmed Sheikh, Happy Mittal +2
Lifted inference reduces the complexity of inference in relational probabilistic models by identifying groups of constants (or atoms) which behave symmetric to each other. A number…
Domain Aware Markov Logic Networks
Happy Mittal, Ayush Bhardwaj, Vibhav Gogate +1
Combining logic and probability has been a long stand- ing goal of AI research. Markov Logic Networks (MLNs) achieve this by attaching weights to formulas in first-order logic, and…