3 papers
cs.AI2026
Do LLMs Build Spatial World Models? Evidence from Grid-World Maze Tasks
Weijiang Li, Yilin Zhu, Rajarshi Das +1
Foundation models have shown remarkable performance across diverse tasks, yet their ability to construct internal spatial world models for reasoning and planning remains unclear. W…
cs.AI2025
Impact of Noise on LLM-Models Performance in Abstraction and Reasoning Corpus (ARC) Tasks with Model Temperature Considerations
Nikhil Khandalkar, Pavan Yadav, Krishna Shinde +2
Recent advancements in Large Language Models (LLMs) have generated growing interest in their structured reasoning capabilities, particularly in tasks involving abstraction and patt…
cs.CL2025
Exploring Next Token Prediction in Theory of Mind (ToM) Tasks: Comparative Experiments with GPT-2 and LLaMA-2 AI Models
Pavan Yadav, Nikhil Khandalkar, Krishna Shinde +2
Language models have made significant progress in generating coherent text and predicting next tokens based on input prompts. This study compares the next-token prediction performa…