repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
Noshkoto/Noshy
Your agent has amnesia. Noshy fixes that. Persistent memory for AI agents — LLM extraction, hybrid search, zero deps.
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.
- LinkedLinked via unknownGoogle DeepMind is worried about what happens when millions of agents start to interact →
- LinkedLinked via unknownI made a superhuman Generals.io agent with self-play RL [P] →
- LinkedLinked via unknownMargaret Atwood says the problem with AI is ‘garbage in, garbage out’ →
- LinkedLinked via unknownEvaluating long-term memory limits in stateless LLM chatbots — feedback needed [D] →
- LinkedLinked via unknownNew Server Hopes to Break Through AI’s “Memory Wall” →
- LinkedLinked via unknownAgent-Native Immune System: Architecture, Taxonomy, and Engineering →
- LinkedLinked via unknownSelective Memory Retention for Long-Horizon LLM Agents →
- LinkedLinked via unknownManufactured Confidence: How Memory Consolidation Turns Hearsay into Confident Facts →
Covers
Covers (incoming)
newsMargaret Atwood says the problem with AI is ‘garbage in, garbage out’newsEvaluating long-term memory limits in stateless LLM chatbots — feedback needed [D]newsNew Server Hopes to Break Through AI’s “Memory Wall”newsI built an open-source memory governance layer for AI assistants - looking for technical feedback [P]newsHidden prompts can plant false memories in AI agents, researchers warn - Tech Xplore
Implements (incoming)
paperAgent-Native Immune System: Architecture, Taxonomy, and EngineeringpaperSelective Memory Retention for Long-Horizon LLM AgentspaperManufactured Confidence: How Memory Consolidation Turns Hearsay into Confident FactspaperAlways-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgentspaperForensic Trajectory Signatures for Agent Memory Poisoning DetectionpaperSelf-Evolving World Models for LLM Agent PlanningpaperECHO: Prune to act, trace to learn with selective turn memory in agentic RLpaperMemSyco-Bench: Benchmarking Sycophancy in Agent Memory
Related across the graph
paperAlways-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgentsnewsHidden prompts can plant false memories in AI agents, researchers warn - Tech XplorenewsI built an open-source memory governance layer for AI assistants - looking for technical feedback [P]paperSelf-Evolving World Models for LLM Agent PlanningnewsNew Server Hopes to Break Through AI’s “Memory Wall”newsEvaluating long-term memory limits in stateless LLM chatbots — feedback needed [D]newsMargaret Atwood says the problem with AI is ‘garbage in, garbage out’paperManufactured Confidence: How Memory Consolidation Turns Hearsay into Confident FactspaperECHO: Prune to act, trace to learn with selective turn memory in agentic RLnewsGoogle DeepMind is worried about what happens when millions of agents start to interactnewsI made a superhuman Generals.io agent with self-play RL [P]paperSelective Memory Retention for Long-Horizon LLM AgentspaperAgent-Native Immune System: Architecture, Taxonomy, and EngineeringpaperMemSyco-Bench: Benchmarking Sycophancy in Agent MemorypaperForensic Trajectory Signatures for Agent Memory Poisoning Detection