Oblivion: Self-Adaptive Agentic Memory Control through Decay-Driven Activation
Summary: arXiv:2604.00131v1 Announce Type: cross
Abstract
Human memory is a complex system that adapts through selective forgetting; experiences gradually become less accessible over time, yet they can be reactivated by reinforcement or contextual cues. In contrast, memory-augmented language model (LLM) agents typically rely on a model that features “always-on” retrieval and “flat” memory storage. This approach leads to high interference and latency as the amount of historical data grows.
Introduction to Oblivion
In response to these challenges, researchers have introduced Oblivion, a novel memory control framework that reconceptualizes forgetting as decay-driven reductions in accessibility rather than explicit deletion. Oblivion effectively decouples memory control into two distinct paths: reading and writing.
Mechanics of Oblivion
- Read Path: This path determines when to consult memory, based on factors such as agent uncertainty and the sufficiency of the memory buffer. By doing so, it avoids the redundancy of continuous access to memory.
- Write Path: The write path is responsible for deciding which memories to reinforce. It strengthens memories that significantly contribute to forming a response, ensuring that only relevant information is preserved.
Hierarchical Memory Organization
By integrating these mechanisms, Oblivion enables a hierarchical organization of memory. This structure allows for the maintenance of persistent high-level strategies while dynamically loading detailed information as required. Such adaptability is crucial in environments where context shifts frequently, providing a more efficient and responsive framework for LLM agents.
Evaluation and Results
The effectiveness of Oblivion was evaluated on both static and dynamic long-horizon interaction benchmarks. The results demonstrated that Oblivion can dynamically adapt memory access and reinforcement, effectively balancing learning and forgetting depending on the context at hand. This adaptability is essential for enhancing the reasoning capabilities of LLM agents.
Conclusion
The introduction of Oblivion signifies a significant step forward in the realm of memory management for LLM agents. By treating memory control as a dynamic and adaptable process, Oblivion highlights the importance of memory management in achieving effective agentic reasoning. For those interested in exploring this framework further, the source code is available at https://github.com/nec-research/oblivion.