Running summarizing tools on a new article

Abstract: While large language models (LLMs) have demonstrated remarkable capabilities, their performance on complex reasoning tasks is often constrained by linear decoding or isolated search topologies. Existing structured prompting methods like Tree of Thoughts (ToT) suffer from path isolation, whereas Graph of Thoughts (GoT) requires complex, manually engineered routing structures. To address these limitations, we introduce Diamond of Thoughts (DoT), a lightweight, plug-and-play prompting framework that enforces a dynamic "diverge-and-merge" topology. DoT systematically generates diverse reasoning branches, extracts the most promising intermediate deductions, and employs a synergistic merge operator to fuse them into a robust consensus state before proceeding to the next reasoning depth. Extensive empirical evaluations in rigorous mathematical reasoning (Game of 24), open-ended text generation (Creative Writing), and complex logical reasoning (Einstein Riddle) demonstrate that DoT consistently achieves excellent performance. Crucially, by strategically investing computational resources into synergistic fusion rather than naive branch expansion, DoT successfully breaks the performance ceiling of traditional heuristic searches, establishing a highly effective paradigm for complex LLM reasoning.