4 papers
OpenRFM: Dissecting Relational In-Context Learning
Zhikai Chen, Junyu Yin, Jialiang Gu +5
Relational Foundation Models (RFMs) promise a single pre-trained predictor that, given any relational database, returns predictions in one forward pass via relational in-context le…
Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline
Zhikai Chen, Jialiang Gu, Junyu Yin +6
LLM agents accumulate histories that outgrow their context windows, motivating a growing literature on memory systems. Yet most existing designs are tuned to a single scenario (mul…
Do Large Language Models Understand Performance Optimization?
Bowen Cui, Tejas Ramesh, Oscar Hernandez +1
Large Language Models (LLMs) have emerged as powerful tools for software development tasks such as code completion, translation, and optimization. However, their ability to generat…
DeepContext: A Context-aware, Cross-platform, and Cross-framework Tool for Performance Profiling and Analysis of Deep Learning Workloads
Qidong Zhao, Hao Wu, Yuming Hao +4
Effective performance profiling and analysis are essential for optimizing training and inference of deep learning models, especially given the growing complexity of heterogeneous c…