Learning Layer Paper Reading Club - Week 29 - HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
This week's paper:
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models
Link:
https://arxiv.org/pdf/2405.14831
Abstract:
Most RAG systems retrieve passages independently. That works well until answering a question requires connecting information scattered across multiple documents.
HippoRAG asks a different question: what if LLM memory worked a little more like human memory?
Inspired by how the hippocampus helps us recall related information, HippoRAG combines LLMs, knowledge graphs, and Personalized PageRank to connect concepts and retrieve relevant information across multiple hops.
The paper shows that this approach can outperform strong RAG baselines on multi-hop question answering while performing the reasoning-heavy retrieval in a single step.
What we’ll discuss:
Why standard RAG struggles when information is spread across documents
How HippoRAG turns text into a graph of connected knowledge
Why Personalized PageRank is useful for retrieval
Where HippoRAG performs well and where it still falls short
What this could mean for long-term memory in AI systems
You do not need a neuroscience background or deep familiarity with the paper. If you work on RAG, agents, knowledge graphs, memory, or LLM infrastructure, there should be plenty to dig into.
The discussion will be guided by Aditya Srivastava, AI Researcher & Engineer at HydraDB and an alumnus of Carnegie Mellon University and IIT Bombay.
What is the Learning Layer Labs Paper Reading Club?
An initiative from https://www.learninglayer.ai, a lab with the goal of reducing AI anxiety in the world.
What is the format?
Discussion based. Expect a low pressure environment to share insights and opinions with the group.
What are the group goals?
Stay on top of AI research and improve understanding of AI fundamentals + math.
Who is welcome?
Everyone! Try to put in at least some time on the paper and come prepared with questions or things you'd like to discuss, but it's ok to just show up!
Learning Layer Labs team:
Thomas Redfern ( The backbone who's at nearly every paper reading )
Mat Allen (The new fella bring order and organization)
Devinder Sodhi (The guy you talk to for sponsoring)
We have a sponsor this week! HydraDB is sponsoring the event.
HomeBrew club is hosting us this week!
About HomeBrew
Homebrew is a 24/7 member-run DIY community space in SF, fostering collaborative co-working, knowledge sharing, and experimentation at the frontier of tech - including AI and other emerging fields.