4 papers
Recall What Is Missing: Composing Evidence from Long-Term Agent Memory
Qi Feng, Jicong Fan
Under a limited context budget, a long-term agent must recall not merely memories that are individually relevant, but evidence that is collectively sufficient for the current query…
The Retriever Should Remember: Experience-Amortized Reranking for Long-Term Agent Memory
Qi Feng, Chris Ding, Jicong Fan
Long-term language-model agents accumulate memories across interactions, but their retrievers typically do not accumulate retrieval experience. Semantic retrieval is efficient, but…
GraphVec: Cross-Domain Graph Vectorization for Graph-Level Representation Learning
Qi Feng, Jicong Fan
Learning universal graph representations across heterogeneous domains is difficult because graph datasets differ in topology, node-attribute semantics, feature dimensions, and even…
GraphProp: Training the Graph Foundation Models using Graph Properties
Ziheng Sun, Qi Feng, Lehao Lin +2
This work focuses on training graph foundation models (GFMs) that have strong generalization ability in graph-level tasks such as graph classification. Effective GFM training requi…