2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.AI2024★ 2 cited
LLM+Reasoning+Planning for Supporting Incomplete User Queries in Presence of APIs
Sudhir Agarwal, Anu Sreepathy, David H. Alonso +1
Recent availability of Large Language Models (LLMs) has led to the development of numerous LLM-based approaches aimed at providing natural language interfaces for various end-user…
cs.CL2024★ 1 cited
TIC: Translate-Infer-Compile for accurate "text to plan" using LLMs and Logical Representations
Sudhir Agarwal, Anu Sreepathy
We study the problem of generating plans for given natural language planning task requests. On one hand, LLMs excel at natural language processing but do not perform well on planni…
cs.LG2023
A Scalable Technique for Weak-Supervised Learning with Domain Constraints
Sudhir Agarwal, Anu Sreepathy, Lalla Mouatadid
We propose a novel scalable end-to-end pipeline that uses symbolic domain knowledge as constraints for learning a neural network for classifying unlabeled data in a weak-supervised…