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Скачать или смотреть Reasoning Models Generate Societies of Thought (Jan 2026)

  • AI Papers Slop
  • 2026-01-21
  • 17
Reasoning Models Generate Societies of Thought (Jan 2026)
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Описание к видео Reasoning Models Generate Societies of Thought (Jan 2026)

Title: Reasoning Models Generate Societies of Thought (Jan 2026)
Link: http://arxiv.org/abs/2601.10825v1
Date: January 2026

Summary:
This study proposes that the enhanced reasoning capabilities of models like DeepSeek-R1 and QwQ-32B emerge from an implicit simulation of multi-agent interactions, termed a "society of thought." By analyzing reasoning traces, the authors find that these models exhibit high perspective diversity and conversational behaviors—such as question-answering, conflict, and reconciliation—mimicking human group dynamics. Mechanistic interpretability experiments show that steering conversational features (e.g., markers of surprise) directly improves reasoning accuracy. Furthermore, reinforcement learning experiments demonstrate that base models spontaneously develop these conversational behaviors when rewarded for accuracy, and that fine-tuning with conversational scaffolding accelerates reasoning improvement compared to monologue-based approaches.

Key Topics:
Large Language Models
Reasoning Models
Chain of Thought
Multi-agent Simulation
Reinforcement Learning
Mechanistic Interpretability
Collective Intelligence
DeepSeek-R1
Socio-emotional Roles

Chapters:
00:00 - Society of Thought Introduction
01:22 - The Enigma of Reason
02:51 - Analyzing Internal Conversations
04:22 - Conflict and Reconciliation Examples
06:14 - Identifying the Eureka Feature
07:11 - Steering Reasoning Accuracy
08:32 - The Anxious Verifier Persona
10:20 - Spontaneous Behavior Emergence
12:40 - The Future of Scaling

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