8 papers
From Context to Skills: Can Language Models Learn from Context Skillfully?
Shuzheng Si, Haozhe Zhao, Yu Lei +10
Many real-world tasks require language models (LMs) to reason over complex contexts that exceed their parametric knowledge. This calls for context learning, where LMs directly lear…
Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans
Yu Lei, Hao Liu, Chengxing Xie +6
As large language models (LLMs) increasingly engage in complex social interactions, ensuring that their behaviors align with human ethical principles and intentions, known as value…
A Unified Framework for Modeling Heterogeneous Financial Data via Dual-Granularity Prompting
Yu Lei, Zixuan Wang, Yiqing Feng +5
Recent industrial credit scoring models remain heavily reliant on manually tuned statistical learning methods. Despite their potential, deep learning architectures have struggled t…
From Context to EDUs: Faithful and Structured Context Compression via Elementary Discourse Unit Decomposition
Yiqing Zhou, Yu Lei, Shuzheng Si +7
Managing extensive context remains a critical bottleneck for Large Language Models (LLMs), particularly in applications like long-document question answering and autonomous agents…
Generative Large-Scale Pre-trained Models for Automated Ad Bidding Optimization
Yu Lei, Jiayang Zhao, Yilei Zhao +4
Modern auto-bidding systems are required to balance overall performance with diverse advertiser goals and real-world constraints, reflecting the dynamic and evolving needs of the i…
RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context
Yu Lei, Shuzheng Si, Wei Wang +4
Large language models are evolving from single-turn responders into tool-using agents capable of sustained reasoning and decision-making for deep research. Prevailing systems adopt…