Table of contents
- 🎮 Part 1: Background and Motivation
- 🎮 Part 2: Game Design and Framework
- 🎮 Part 3: Learning Strategies and Training
- 🎮 Part 4: Experimental Evaluation
- 🎮 Part 5: Discussion and Future Directions
Self-Playing Adversarial Language Game (SPAG) is a novel approach to improve the reasoning capabilities of Large Language Models (LLMs). By framing language interactions as an adversarial game—where one agent tries to induce the other to utter a hidden target word—it encourages nuanced strategic thinking and deeper logical inference.
In this series, we walk through the SPAG paper from the ideas behind the design to the key results presented in evaluation, with a final look into what this paper tells us about the future of LLM reasoners.
A Deep Research series