3 papers
cs.AI2026
pro-team at LLMs4OL 2026 Tasks Flagship and Reuse: Retrieval-Augmented Generation and Vocabulary-Constrained Filtering for Ontology Learning
Shivam Mishra, Dhannu Ram Meena, Muneendra Ojha +2
Ontology learning from text remains challenging despite significant progress in Large Language Models (LLMs), which can hallucinate domain terms, produce inconsistent formats, and…
cs.LG2025
SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
Satyam Mishra, Phung Thao Vi, Shivam Mishra +3
We introduce SafeRL-Lite, an open-source Python library for building reinforcement learning (RL) agents that are both constrained and explainable. Existing RL toolkits often lack n…
cs.CV2024
GAN Based Top-Down View Synthesis in Reinforcement Learning Environments
Usama Younus, Vinoj Jayasundara, Shivam Mishra +1
Human actions are based on the mental perception of the environment. Even when all the aspects of an environment are not visible, humans have an internal mental model that can gene…