Self-Anchor: keep LLMs focused through long reasoning

Kari Jaaskelainen

06 Oct 2025

When chains get long, LLMs lose the thread. Self-Anchor pins it down.

Self-Anchor structures a plan from the reasoning trajectory and automatically aligns the model’s attention to the most relevant steps while generating. Across six benchmarks, it outperforms state-of-the-art prompting and narrows the gap between general and specialized reasoning models—without retraining.

Why it matters: Better attention guidance means fewer mid-chain stumbles and more reliable answers.

Imagine trail markers on a foggy hike—the path stays visible. 🧭🧩🌫️

See how step-by-step attention alignment stabilizes complex reasoning, then try it on your toughest tasks.

Paper: http://arxiv.org/abs/2510.03223v1

Register: https://www.AiFeta.com

Paper: http://arxiv.org/abs/2510.03223v1

Register: https://www.AiFeta.com

#LLM #PromptEngineering #Reasoning #NLP #AIResearch #Attention #ChainOfThought

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