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  1. Home
  2. /Repositories
  3. /sandst1/remind
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago

sandst1/remind

A memory layer for AI Agents

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 60%MemSyco-Bench: Benchmarking Sycophancy in Agent Memory →
  • PossiblePossibly related (embedding) · 60%AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents →
  • PossiblePossibly related (embedding) · 59%Self-Evolving World Models for LLM Agent Planning →
  • PossiblePossibly related (embedding) · 57%AutoTrainess: Teaching Language Models to Improve Language Models Autonomously →
  • PossiblePossibly related (embedding) · 57%I built an open-source memory governance layer for AI assistants - looking for technical feedback [P] →
  • PossiblePossibly related (embedding) · 56%We're building agents that can read millions of documents, but still forget a video they watched yesterday. →
  • PossiblePossibly related (embedding) · 60%MRMS: A Multi-Resolution Memory Substrate for Long-Lived AI Agents →
  • PossiblePossibly related (embedding) · 53%Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade →

Implements

paperMemSyco-Bench: Benchmarking Sycophancy in Agent MemorypaperAgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM AgentspaperSelf-Evolving World Models for LLM Agent PlanningpaperAutoTrainess: Teaching Language Models to Improve Language Models Autonomously

Covers

newsI built an open-source memory governance layer for AI assistants - looking for technical feedback [P]

Covers (incoming)

newsWe're building agents that can read millions of documents, but still forget a video they watched yesterday.newsChoosing the Right AI Agent Memory Strategy: A Decision-Tree Approach

Implements (incoming)

paperMRMS: A Multi-Resolution Memory Substrate for Long-Lived AI AgentspaperDoomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe CascadepaperLatent Memory Palace: Reasoning for Control as Autoregressive Variational InferencepaperRemember When It Matters: Proactive Memory Agent for Long-Horizon AgentspaperFunction-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation ModelspaperHuman-AI Agent Interaction as a Neuroplastic Training Environment

Related across the graph

newsWe're building agents that can read millions of documents, but still forget a video they watched yesterday.newsI built an open-source memory governance layer for AI assistants - looking for technical feedback [P]paperMRMS: A Multi-Resolution Memory Substrate for Long-Lived AI AgentspaperAgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM AgentsnewsChoosing the Right AI Agent Memory Strategy: A Decision-Tree ApproachpaperSelf-Evolving World Models for LLM Agent PlanningpaperRemember When It Matters: Proactive Memory Agent for Long-Horizon AgentspaperDoomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe CascadepaperAutoTrainess: Teaching Language Models to Improve Language Models AutonomouslypaperFunction-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation ModelspaperHuman-AI Agent Interaction as a Neuroplastic Training EnvironmentpaperMemSyco-Bench: Benchmarking Sycophancy in Agent MemorypaperLatent Memory Palace: Reasoning for Control as Autoregressive Variational Inference
Knowledge path·NWe're building agents that can read millions of documents, but still forget a video they watched yesterday.→NI built an open-source memory governance layer for AI assistants - looking for technical feedback [P]→PMRMS: A Multi-Resolution Memory Substrate for Long-Lived AI Agents→Rsandst1/remind

Topics

agentic-aiagentsaicodingcontext-engineeringgenaillmlong-term-memorymcpmcp-server

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Graph trust82Primary
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