6 papers
SAKE: Structured Agentic Knowledge Extrapolation for Complex LLM Reasoning via Reinforcement Learning
Jiashu He, Jinxuan Fan, Bowen Jiang +4
Knowledge extrapolation is the process of inferring novel information by combining and extending existing knowledge that is explicitly available. It is essential for solving comple…
Think Twice Before You Write -- an Entropy-based Decoding Strategy to Enhance LLM Reasoning
Jiashu He, Meizhu Liu, Olaitan P Olaleye +9
Decoding strategies play a central role in shaping the reasoning ability of large language models (LLMs). Traditional methods such as greedy decoding and beam search often suffer f…
TransportAgents: a multi-agents LLM framework for traffic accident severity prediction
Zhichao Yang, Jiashu He, Jinxuan Fan +1
Accurate prediction of traffic crash severity is critical for improving emergency response and public safety planning. Although recent large language models (LLMs) exhibit strong r…
PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
Bowen Jiang, Yuan Yuan, Maohao Shen +13
Personalization is one of the next milestones in advancing AI capability and alignment. We introduce PersonaMem-v2, the state-of-the-art dataset for LLM personalization that simula…
E-bike agents: Large Language Model-Driven E-Bike Accident Analysis and Severity Prediction
Zhichao Yang, Jiashu He, Mohammad B. Al-Khasawneh +2
E-bikes have rapidly gained popularity as a sustainable form of urban mobility, yet their safety implications remain underexplored. This paper analyzes injury incidents involving e…
GeoGrid-Bench: Can Foundation Models Understand Multimodal Gridded Geo-Spatial Data?
Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang +6
We present GeoGrid-Bench, a benchmark designed to evaluate the ability of foundation models to understand geo-spatial data in the grid structure. Geo-spatial datasets pose distinct…