6 papers
MODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning
Shang Ma, Jisheng Dang, Wencan Zhang +6
We propose a multi-agent collaborative framework built upon a lightweight Multimodal Large Language Model (MLLM), specifically designed for social intelligence reasoning. A key fea…
On the Diagram of Thought
Yifan Zhang, Yang Yuan, Andrew Chi-Chih Yao
Large Language Models (LLMs) excel at many tasks but often falter on complex problems that require structured, multi-step reasoning. We introduce the Diagram of Thought (DoT), a fr…
Group Representational Position Encoding
Yifan Zhang, Zixiang Chen, Yifeng Liu +6
We present GRAPE (Group Representational Position Encoding), a unified framework for positional encoding based on group actions. GRAPE unifies two families of mechanisms: (i) multi…
On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning
Yifan Zhang, Yifeng Liu, Huizhuo Yuan +3
Policy gradient algorithms have been successfully applied to enhance the reasoning capabilities of large language models (LLMs). KL regularization is ubiquitous, yet the design sur…
Meta Prompting for AI Systems
Yifan Zhang, Yang Yuan, Andrew Chi-Chih Yao
We introduce Meta Prompting (MP), a framework that emphasizes the formal structure of a task rather than content-specific worked examples. We give a categorical formalization in wh…
Autonomous Data Selection with Zero-shot Generative Classifiers for Mathematical Texts
Yifan Zhang, Yifan Luo, Yang Yuan +1
We present Autonomous Data Selection (AutoDS), a method that leverages base language models themselves as zero-shot "generative classifiers" to automatically curate high-quality ma…