6 citations · 22 across the 16 of their papers we have counts for
7 papers · 1 filter
Improving Neural Ranking Models with Traditional IR Methods
Anik Saha, Oktie Hassanzadeh, Alex Gittens +3
Neural ranking methods based on large transformer models have recently gained significant attention in the information retrieval community, and have been adopted by major commercia…
A Cross-Domain Evaluation of Approaches for Causal Knowledge Extraction
Anik Saha, Oktie Hassanzadeh, Alex Gittens +3
Causal knowledge extraction is the task of extracting relevant causes and effects from text by detecting the causal relation. Although this task is important for language understan…
LakeBench: Benchmarks for Data Discovery over Data Lakes
Kavitha Srinivas, Julian Dolby, Ibrahim Abdelaziz +6
Within enterprises, there is a growing need to intelligently navigate data lakes, specifically focusing on data discovery. Of particular importance to enterprises is the ability to…
Generalized Planning in PDDL Domains with Pretrained Large Language Models
Tom Silver, Soham Dan, Kavitha Srinivas +3
Recent work has considered whether large language models (LLMs) can function as planners: given a task, generate a plan. We investigate whether LLMs can serve as generalized planne…
Some congruences for and -regular partitions
T Kathiravan, K Srinivas, Usha K Sangale
Let count the number of , -regular partitions respectively. In this paper we shall derive infinite families of congruen…
A Vision for Semantically Enriched Data Science
Udayan Khurana, Kavitha Srinivas, Sainyam Galhotra +1
The recent efforts in automation of machine learning or data science has achieved success in various tasks such as hyper-parameter optimization or model selection. However, key are…
Serenity: Library Based Python Code Analysis for Code Completion and Automated Machine Learning
Wenting Zhao, Ibrahim Abdelaziz, Julian Dolby +3
Dynamically typed languages such as Python have become very popular. Among other strengths, Python's dynamic nature and its straightforward linking to native code have made it the…