5 papers
SARIA: Persistence-Aware KV Caching with Coordinated DRAM--SSD Reload for LLM Agents
Hui Li, Qihui Zhou, Xiao Yan +7
Multi-turn LLM agents usually reuse long context prefixes, making key value (KV) caching crucial for reducing prefill latency. SSDs provide a low-cost extension to limited DRAM cap…
Metis: Bridging Text and Code Memory for Self-Evolving Agents
Zijie Dai, Siuhin He, Hui Li +9
Self-evolving agents improve over time by distilling experience from past executions and reusing it in future tasks. Existing systems represent such experience either as natural-la…
RecMem: Recurrence-based Memory Consolidation for Efficient and Effective Long-Running LLM Agents
Zijie Dai, Shiyuan Deng, Sheng Guan +4
Memory systems often organize user-agent interactions as retrievable external memory and are crucial for long-running agents by overcoming the limited context windows of LLMs. Howe…
RLDBF: Enhancing LLMs Via Reinforcement Learning With DataBase FeedBack
Weichen Dai, Zijie Dai, Zhijie Huang +6
While current large language models (LLMs) demonstrate remarkable linguistic capabilities through training on massive unstructured text corpora, they remain inadequate in leveragin…
KALE-LM-Chem: Vision and Practice Toward an AI Brain for Chemistry
Weichen Dai, Yezeng Chen, Zijie Dai +9
Recent advancements in large language models (LLMs) have demonstrated strong potential for enabling domain-specific intelligence. In this work, we present our vision for building a…