Natural Language Reasoning Problem

Natural language reasoning (NLR) focuses on enabling computers to understand and reason with human language, aiming to bridge the gap between human-like comprehension and machine processing of textual information. Current research emphasizes improving the robustness and interpretability of large language models (LLMs) for NLR tasks, exploring techniques like causal analysis to understand model biases and integrating LLMs with symbolic reasoning methods such as logic programming to enhance accuracy and generalizability. These advancements hold significant potential for improving various applications, including question answering, knowledge acquisition, and automated problem-solving across diverse domains.