Semanlink - LLM AND Language Models + Knowledge

Printer friendly

Search Tag:

Search Doc:

Preferences...

Tag Cloud

Andrew Ng - Arxiv Doc - Benchmark - Cheat sheet - Dean Allemang - Denny Vrandečić - Discuté avec Raphaël - DSPy (Demonstrate-Search-Predict) - Fine-tuning - Frank van Harmelen - GitHub project - Graph database - Information retrieval - J'y étais - Jerry Liu - Juan Sequeda - Knowledge Graphs - Knowledge-Intensive NLP Tasks - Knowledge management - LangChain - Language Models + Knowledge - LlamaIndex - LLM - LLM + KG - LM + Search - LM evaluation - Microsoft Research - Named Entity Recognition - NLP@Amazon - NLP@Meta - NLP@Microsoft - NLP@Stanford - NLP based IR - Not Encoding Factual Knowledge in Language Model - Omar Khattab - Personal assistant - Prompting/In-context learning - Prompts - RAG (Retrieval-Augmented Generation) - RAG + KG - Retrieval augmented LM - Retriever-Reader - Sample code - Slides - Survey / Review - Tweet - Webinar - Wikimedia - YouTube video -

LLM AND Language Models + Knowledge

Common descendants

31 Documents

Tags:

2024-04-12 About

Leonie sur X : "Ollama allows you to run open source LLMs LOCALLY..."

Tags:

2024-03-30 About

DSPy Cheatsheet | DSPy

Tags:

2024-03-30 About

Enhancing RAG-based application accuracy by constructing and leveraging knowledge graphs

Tags:

2024-03-16 About

Frank van Harmelen sur X : "...GenAI is rapidly becoming the best motivation for symbolic AI in a long time!"

Tags:

2024-03-15 About

Krista Opsahl-Ong sur X : "Got a pipeline with **multiple prompts**, like a DSPy program? ... Introducing MIPRO, a Multi-prompt Instruction Proposal Optimizer...."

Tags:

2024-03-09 About

KGC23 Keynote: The Future of Knowledge Graphs in a World of LLMs — Denny Vrandečić, Wikimedia - YouTube

Tags:

2024-03-07 About

GraphRAG: Unlocking LLM discovery on narrative private data - Microsoft Research

Tags:

2024-03-07 About

Intro to DSPy: Goodbye Prompting, Hello Programming! | by Leonie Monigatti | Feb, 2024 | Towards Data Science

Tags:

DSPy (Demonstrate-Search-Predict)

2024-03-01 About

Omar Khattab sur X : "...Let's use 30 lines of DSPy—without any hand-written prompts or any calls to OpenAI ($0)—to teach..."

Tags:

2024-01-01 About

[2311.07509] A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databases

Tags:

2023-11-21 About

Fine-tuning with Retrieval Augmentation - LlamaIndex

Tags:

2023-10-07 About

[2310.01352] RA-DIT: Retrieval-Augmented Dual Instruction Tuning

Tags:

2023-10-07 About

Jerry Liu sur X : "seven full ways to query knowledge graphs with LLMs..."

Tags:

2023-09-30 About

[2309.15427] Graph Neural Prompting with Large Language Models

Tags:

> Can we learn beneficial knowledge from KGs
and integrate them into pre-trained LLMs?

> we propose to
leverage the factual knowledge from KGs to enhance LLMs,
while still benefiting from circumventing the burdensome
training expenses by using pre-trained LLMs

> Graph Neural Prompting
(GNP), a plug-and-play method to assist pre-trained
LLMs in learning beneficial knowledge from KGs
>
> GNP
encodes the pertinent grounded knowledge and complex
structural information to derive Graph Neural Prompt, an
embedding vector that can be sent into LLMs to provide
guidance and instructions

> - GNP first utilizes
a GNN to capture and encode the
intricate graph knowledge into **entity/node embeddings**. 
> - Then,
a cross-modality pooling module is present to determine
the **most relevant node embeddings in relation to the text
input**, and consolidate these node embeddings into **a holistic
graph-level embedding**.
> - After that, GNP encompasses a
**domain projector** to bridge the inherent disparities between
the graph and text domains.
> - Finally, a **self-supervised link
prediction objective** is introduced to enhance the model
comprehension of relationships between entities and capture
graph knowledge in a self-supervised manner.

2023-09-28 About

Inside DSPy: The New Language Model Programming Framework You Need… – Towards AI

Tags:

DSPy (Demonstrate-Search-Predict)

2023-09-06 About

Omar Khattab sur X : "Announcing 𝗗𝗦𝗣y..."

Tags:

2023-08-24 About

Knowledge Graph RAG Query Engine - LlamaIndex

Tags:

2023-08-17 About

Jerry Liu on X: “Graph RAG” in @llama_index: a new method of augmenting LLMs with context from a graph database

Tags:

2023-08-17 About

GitHub - neo4j/NaLLM: Repository for the NaLLM project

Tags:

2023-08-14 About

Knowledge Graphs & LLMs: Fine-Tuning Vs. Retrieval-Augmented Generation | by Tomaz Bratanic | Neo4j Developer Blog (June 6 2023)

Tags:

2023-08-13 About

ML Blog - Improve ChatGPT with Knowledge Graphs

Tags:

2023-07-04 About

[2212.14024] Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Tags:

2023-06-23 About

[2306.08302] Unifying Large Language Models and Knowledge Graphs: A Roadmap

Tags:

2023-06-18 About

Jerry Liu sur Twitter : "The DSP project carries a lot of insights for improving RAG..."

Tags:

2023-06-18 About

Retrieval-augmented LMs, and prompting

Tags:

2023-06-16 About

LangChain Retrieval Webinar - YouTube

Tags:

2023-05-27 About

Jerry Liu sur Twitter : "To evaluate retrieval-augmented LLM’s, we can compare the query/response/source context to see if they match. We just added this to @gpt_index..."

Tags:

2023-04-11 About

stanfordnlp/dspy: 𝗗𝗦𝗣: Demonstrate-Search-Predict. A framework for composing retrieval and language models for knowledge-intensive NLP.

Tags:

2023-02-18 About

deepset sur Twitter : " Generative models have taken the world of NLP by storm. But LLMs do not know about your personal data. This makes personal assistants, enterprise knowledge management and many other applications challenging. Retrieval augmented pipelines are the answer"

Tags:

2023-02-02 About

Akari Asai sur Twitter : "Can we solely rely on LLMs’ memories (eg replace search w ChatGPT)? Probably not... Our analysis shows how retrieval is complementary to LLMs’ parametric knowledge..."

Tags:

2022-12-21 About