3 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
Code-driven Number Sequence Calculation: Enhancing the inductive Reasoning Abilities of Large Language Models
Kedi Chen, Zhikai Lei, Xu Guo +10
Large language models (LLMs) make remarkable progress in reasoning tasks. Among different reasoning modes, inductive reasoning, due to its better alignment with human learning, att…
A Survey of Inductive Reasoning for Large Language Models
Kedi Chen, Dezhao Ruan, Yuhao Dan +12
Reasoning is an important task for large language models (LLMs). Among all the reasoning paradigms, inductive reasoning is one of the fundamental types, which is characterized by i…
Beyond Quality: Unlocking Diversity in Ad Headline Generation with Large Language Models
Chang Wang, Siyu Yan, Depeng Yuan +8
The generation of ad headlines plays a vital role in modern advertising, where both quality and diversity are essential to engage a broad range of audience segments. Current approa…
Exploring Mathematical Extrapolation of Large Language Models with Synthetic Data
Haolong Li, Yu Ma, Yinqi Zhang +2
Large Language Models (LLMs) have shown excellent performance in language understanding, text generation, code synthesis, and many other tasks, while they still struggle in complex…