5 papers
Learning to Ponder: Adaptive Reasoning in Latent Space
Yixin He, Lumingyuan Tang
Test-time compute has emerged as a key paradigm for enhancing LLM reasoning, yet prevailing approaches like Best-of-N and majority voting apply uniform depth across inputs, wasting…
TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis
Wen Ye, Wei Yang, Defu Cao +4
Time series analysis is crucial in real-world applications, yet traditional methods focus on isolated tasks only, and recent studies on time series reasoning remain limited to eith…
Context Graph
Chengjin Xu, Muzhi Li, Cehao Yang +4
Knowledge Graphs (KGs) are foundational structures in many AI applications, representing entities and their interrelations through triples. However, triple-based KGs lack the conte…
On the Evolution of Knowledge Graphs: A Survey and Perspective
Xuhui Jiang, Chengjin Xu, Yinghan Shen +6
Knowledge graphs (KGs) are structured representations of diversified knowledge. They are widely used in various intelligent applications. In this article, we provide a comprehensiv…
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang +6
Although large language models (LLMs) have achieved significant success in various tasks, they often struggle with hallucination problems, especially in scenarios requiring deep an…