arXiv AI
Aug 6
MemSIF: From Structured Interactions to Dual-Track Fact Memory for LLM Agents
arXiv:2608. 01742v2 Announce Type: replace Abstract: Long-term memory is critical for LLM agents operating over long-horizon interactions.
MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing
arXiv:2605. 23986v2 Announce Type: replace-cross Abstract: Memory is a fundamental component for long-context LLM agents, supporting persistent state across interactions through a continuous serve-and-update lifecycle.
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arXiv AI
Jun 10
Less Context, More Accuracy: A Bi-Temporal Memory Engine for LLM Agents Where a Lean Retrieved Context Beats the Full History
arXiv:2606. 09900v1 Announce Type: cross Abstract: Long-term memory is the missing layer for LLM agents: across sessions they forget, and the common workaround -- replaying the whole history into the prompt -- is expensive, slow, and, as distractors accumulate, less accurate.
arXiv AI
Jul 8
Akashic: A Low-Overhead LLM Inference Service with MemAttention
arXiv:2607. 05708v1 Announce Type: new Abstract: Recent LLM-based agent systems continuously accumulate context across multi-turn interactions, tool invocations, and cross-session workflows.
Hugging Face Trending Papers
Jul 7
Akashic: A Low-Overhead LLM Inference Service with MemAttention
Recent LLM-based agent systems continuously accumulate context across multi-turn interactions, tool invocations, and cross-session workflows. Replaying the full history for every request quickly becomes impractical: long contexts increase prefill cost, may exceed context limits, and often bury task-relevant evidence in irrelevant content, degrading both serving efficiency and output quality.
arXiv AI
Jul 16
Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents
arXiv:2607. 13591v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks.
arXiv AI
Jul 28
ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control
arXiv:2607. 22962v1 Announce Type: new Abstract: LLM agents that operate over many turns accumulate facts in an external memory store and reuse them as premises for downstream reasoning.
arXiv AI
Aug 12
Self-Correcting Long-Horizon Search Agents via Tree-Structured Memory
arXiv:2608. 10676v1 Announce Type: new Abstract: Large language model (LLM)-based search agents answer questions through multi-step interactions with external environments.
arXiv AI
Aug 5
LeanMem: Simple and Efficient Long-Term Memory for LLM Agents
arXiv:2608. 03463v1 Announce Type: new Abstract: Long-term memory is essential for LLM-based agents to sustain interactions and reliably leverage distant history.
arXiv Machine Learning
Aug 4
Stop When Memory Suffices: Evidence-Conditioned Progressive Execution for LLM Agents
arXiv:2608. 01285v1 Announce Type: new Abstract: The continued development of LLMs toward persistent and adaptive intelligence increasingly requires long-term memory mechanisms that preserve and reuse information across interactions.
arXiv AI
Aug 11
SodaMem: Evidence-Grounded Temporal Graph Memory for LLM Agents
arXiv:2608. 08055v1 Announce Type: new Abstract: Large language model (LLM) agents that assist users over weeks of conversation must remember what is currently true, not merely what was once said.
arXiv AI
Jun 12
MemRefine: LLM-Guided Compression for Long-Term Agent Memory
arXiv:2606. 13177v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly expected to operate over long-term interactions, where information from past dialogues must be preserved and recalled to support future tasks.
Hugging Face Trending Papers
Jul 15
Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents
Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approaches, from graph-structured memories to reflective insight stores, access memory through fixed, hand-designed heuristics.