arXiv Machine Learning
Cortex: Consolidating Context into Parametric Memory
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arXiv Machine Learning
Jul 13
Memory-Managed Long-Context Attention: Bounded Editable Memory with a Hard Lifecycle and Calibrated Sparse Fallback
arXiv:2606. 28876v2 Announce Type: replace-cross Abstract: We study memory-managed long-context attention: explicit bounded memory with a learned query-independent writer, lifecycle control, query-aware reading, calibrated sparse fallback, and frozen-LLM generation from raw evidence.
arXiv Computation and Language
Aug 25
Dual-Layer Agentic Memory with Fast Write Routing and Slow Consolidation
arXiv:2608.22215v1 Announce Type: new Abstract: Large language model (LLM) agents operate in dynamic environments where knowledge continuously evolves. Existing memory systems typically treat externa...
arXiv AI
Oct 9
REMORY: Learning Residual Memory for Context Compaction
REMORY is a neural memory network that augments a textual summary of an agent’s history with a small set of soft memory tokens. These tokens, conditioned on the summary, enable a frozen large language model to approximate the continuation it would generate using the full history, effectively acting as a residual connection along the sequence dimension. Experiments on SummHay and long‑horizon agent benchmarks show that REMORY improves source attribution, maintains insight coverage, and achieves near full‑context performance while using only 5.2% of the input positions, while also reducing repeated tool outputs and errors on BrowseComp and Terminal‑Bench 2.1.
arXiv AI
3d ago
Write What Matters: Disentangling Token Selection from Slot Allocation in Recurrent Memory
arXiv:2610.34180v1 Announce Type: cross Abstract: Long-sequence models must retain earlier information. Full attention keeps all past tokens but grows expensive, and recurrent-memory models compress...
arXiv Machine Learning
Aug 14
MARCH: Scaling Recurrent Memory with Content-Routed State Anchors
arXiv:2608. 12435v1 Announce Type: new Abstract: Transformers owe much of their strong long-context retrieval capability to a token-level memory that grows with context length.
arXiv AI
Jul 3
Multi-Head Recurrent Memory Agents
arXiv:2607. 01523v1 Announce Type: cross Abstract: Recurrent memory agents extend LLMs to arbitrarily long contexts by iteratively consolidating input into a fixed-size memory window.