42 citations · 53 across the 8 of their papers we have counts for
9 papers
SRAG: RAG with Structured Data Improves Vector Retrieval
Shalin Shah, Srikanth Ryali, Ramasubbu Venkatesh
Retrieval Augmented Generation (RAG) provides the necessary informational grounding to LLMs in the form of chunks retrieved from a vector database or through web search. RAG could…
Multi-Document Financial Question Answering using LLMs
Shalin Shah, Srikanth Ryali, Ramasubbu Venkatesh
We propose two new methods for multi-document financial question answering. First, a method that uses semantic tagging, and then, queries the index to get the context (RAG_SEM). An…
Multi-Task Triplet Loss for Named Entity Recognition using Supplementary Text
Ryan Siskind, Shalin Shah
Retail item data contains many different forms of text like the title of an item, the description of an item, item name and reviews. It is of interest to identify the item name in…
Multi-Task Learning of Query Intent and Named Entities using Transfer Learning
Shalin Shah, Ryan Siskind
Named entity recognition (NER) has been studied extensively and the earlier algorithms were based on sequence labeling like Hidden Markov Models (HMM) and conditional random fields…
Analysis of Greenhouse Gases
Shalin Shah
Climate change is a result of a complex system of interactions of greenhouse gases (GHG), the ocean, land, ice, and clouds. Large climate change models use several computers and so…
Hebbian Graph Embeddings
Shalin Shah, Venkataramana Kini
Representation learning has recently been successfully used to create vector representations of entities in language learning, recommender systems and in similarity learning. Graph…
Genetic Algorithm for the 0/1 Multidimensional Knapsack Problem
Shalin Shah
The 0/1 multidimensional knapsack problem is the 0/1 knapsack problem with m constraints which makes it difficult to solve using traditional methods like dynamic programming or bra…
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
Jianfeng Gao, Qiang Wu, Chris Burges +5
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The resu…
Genetic Algorithm for a class of Knapsack Problems
Shalin Shah
The 0/1 knapsack problem is weakly NP-hard in that there exist pseudo-polynomial time algorithms based on dynamic programming that can solve it exactly. There are also the core bra…