The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …

Abstract The 5th Generation (5G) and beyond networks are expected to offer huge
throughputs, connect large number of devices, support low latency and large numbers of …

We introduce SwiftSage, a novel agent framework inspired by the dual-process theory of
human cognition, designed to excel in action planning for complex interactive reasoning …

We present ScienceWorld, a benchmark to test agents' scientific reasoning abilities in a new
interactive text environment at the level of a standard elementary school science curriculum …

A wide range of real-world applications is characterized by their symbolic nature,
necessitating a strong capability for symbolic reasoning. This paper investigates the …

Deep reinforcement learning (RL) methods often require many trials before convergence,
and no direct interpretability of trained policies is provided. In order to achieve fast …

We focus on creating agents that act in alignment with socially beneficial norms and values
in interactive narratives or text-based games--environments wherein an agent perceives and …

Advancements in generative AI have broadened the potential applications of Large
Language Models (LLMs) in the development of autonomous agents. Achieving true …

World models improve a learning agent's ability to efficiently operate in interactive and
situated environments. This work focuses on the task of building world models of text-based …

Abstract The Abstraction and Reasoning Corpus (ARC)(Chollet, 2019) and its most recent
language-complete instantiation (LARC) has been postulated as an important step towards …