9 papers
Learning Agent-Compatible Context Management for Long-Horizon Tasks
Lu Yi, Runlin Lei, Liuyi Yao +6
LLM agents increasingly face long-horizon tasks such as web search and deep research in real-world applications, where accumulated context can cause long-context degradation and re…
Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents
Yi Yu, Liuyi Yao, Yuexiang Xie +4
Large language model (LLM) agents face fundamental limitations in long-horizon reasoning due to finite context windows, making effective memory management critical. Existing method…
Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data
Zhenqing Ling, Daoyuan Chen, Liuyi Yao +3
Fine-tuning large language models (LLMs) using diverse datasets is crucial for enhancing their overall performance across various domains. In practical scenarios, existing methods…
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Dawei Gao, Zitao Li, Yuexiang Xie +20
Driven by rapid advancements of Large Language Models (LLMs), agents are empowered to combine intrinsic knowledge with dynamic tool use, greatly enhancing their capacity to address…
Security Tensors as a Cross-Modal Bridge: Extending Text-Aligned Safety to Vision in LVLM
Shen Li, Liuyi Yao, Wujia Niu +2
Large visual-language models (LVLMs) integrate aligned large language models (LLMs) with visual modules to process multimodal inputs. However, the safety mechanisms developed for t…
Enhancing Tool Learning in Large Language Models with Hierarchical Error Checklists
Yue Cui, Liuyi Yao, Shuchang Tao +4
Large language models (LLMs) have significantly advanced natural language processing, particularly through the integration of external tools and APIs. However, their effectiveness…