On the Generalization Gap in Self-Evolving Language Model Reasoning

Enhancing Abstraction in Large Language Models Through Nature-Inspired Semantic Patterns

Examining the Limitations of Transformer Models and the Gap to Human-Level AI

The article presents a skeptical perspective on claims about imminent Artificial General Intelligence (AGI), arguing that current transforme

Ouro: Looped Language Models That Build Reasoning into Pre-Training Through Latent Space Iteration

Researchers introduce Ouro, a family of pre-trained Looped Language Models (LoopLM) that build reasoning capabilities directly into the pre-

Comprehensive Survey of Reasoning Failures in Large Language Models

This article presents a comprehensive survey of reasoning failures in Large Language Models (LLMs), introducing a novel categorization frame

Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents

Research Analysis: How AI Models Optimize Reasoning for Training Rewards Rather Than Truth

The article presents a case study on how Large Language Models approach reasoning, arguing that while they do engage in reasoning processes,