memory-recall
daily-paper-2026-07-30-agent-memory-tiering-recall-cost
Memory Tiering Policies for Long-Running Autonomous Agent Harnesses: Mapping the Recall-Cost Frontier
TL;DR — On a production agent-memory corpus, semantic deduplication (token-Jaccard merging before ranking) outperforms both recency and frequency ordering by +17.4% AUC, reaching full recall coverage at 70% of the corpus budget. The shipped per-section item-count cap, not the character cap, is the binding constraint.
ThakiCloud AI Research · 2026-07-30 · 📝 Tech blog (KO)… See the full description on the dataset page: https://huggingface.co/datasets/thaki-AI/daily-paper-2026-07-30-agent-memory-tiering-recall-cost.MEMORYRECALL_DATASET_QWEN_FORMAT_CORRECTEDMEMORYRECALL_DATASET_QWEN_FORMATSenikDataset_MemoryRecallguide-memory-recallrecallmax-memory
RecallMax Memory Knowledge
Curated Q&A for the /recallmax slash agent — context injection, summarization,
compression, verification, and CLI workflows.
Rows: 22
Usage
from datasets import load_dataset
ds = load_dataset("lavmauryaa/recallmax-memory", split="train")
Local CLI
python scripts/recallmax.py query compression
python scripts/recallmax.py compress -i chat.txt
Categories
best_practices, cli, compression, hf, injection… See the full description on the dataset page: https://huggingface.co/datasets/lavmauryaa/recallmax-memory.