Analyzed 535 queries across seven models, finding reasoning traces from under 1 KB to over 71 KB per query. The project develops co-location and indexing strategies for highly variable semantic reasoning workloads.
An analysis of 535 queries across seven models finds reasoning traces ranging from under 1 KB to over 71 KB per query. The project develops co-location and indexing strategies for highly variable semantic reasoning workloads.
@inproceedings{khan2026agentmemory,title={Agent Memory: Storage and Retrieval of LLM Reasoning Traces at Scale},author={Khan, Saman Bahzad and others},booktitle={Conference on Machine Learning and Systems (MLSys)},year={2027},note={Under Submission},}