5 papers
PACMI: Provenance-Aware Cascading Memory Invalidation for Long-Term LLM Agents
Yiqi Wang, Jiaqi Liu, Jiaqi Zhang +4
LLM agents rely on long-term memory to retain and reuse information when performing tasks over long horizons. Existing methods provide limited support for handling memories that be…
MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflows
Yiqi Wang, Zihao Yan, Jiaqi Zhang +5
Shared memory helps language-model agents reuse information across long workflows, yet relevant evidence may not be admissible for a particular agent or action. Because restriction…
From Faulty Memories to Corrected Actions: Dependency-Guided Rollback Repair for Memory-Augmented Agents
Caili Yu, Yiqi Wang, Jiaqi Zhang +5
Persistent memory lets language model agents reuse information across sessions, but it also makes errors durable: a poisoned, stale, or misattributed record can alter reasoning, to…
From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents
Yiqi Wang, Jiaqi Zhang, Zhangkai Wu +9
Large language model (LLM)-based agents are moving beyond text generation to planning, tool use, retrieval, memory access, environmental interaction, and multi-agent collaboration.…
C-World: A Computer Use Agent Environment Creator
Ziqiao Xi, Shuang Liang, Qi Liu +9
To close the gap between LLM-based agents and humans in planning and reasoning, agents need large-scale, diverse environments for continuous learning -- yet building such environme…