Semanlink - Favoris ; AI girls and guys AND Retrieval-based NLP

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Mots-clés liés

@jobergum - Arxiv Doc - ColBERT - Discuté avec Raphaël - DSPy (Demonstrate-Search-Predict) - Embedding Model Fine-tuning - Gautier Izacard - GitHub project - Jerry Liu - Knowledge-augmented Language Models - Knowledge distillation - Knowledge-Intensive NLP Tasks - LangChain - LlamaIndex - LLM - LLMs over your data - LM + Search - LM evaluation - Long documents - Michael Glass - Multi-Vector Retrieval - Neural Search - NLP@ENS - NLP@Facebook - NLP@Stanford - NLP based IR - Not Encoding Factual Knowledge in Language Model - Omar Khattab - pdf parsing - Prompting/In-context learning - Prompts - Question Answering - RAG: chunking - RAG (Retrieval-Augmented Generation) - RAGatouille - Raphaël Sourty - Retrieval augmented LM - Retrieval-based NLP - Retriever-Reader - Sample code - Slot filling - Sparse retrieval - Tables - Text Embeddings - Tips - Tweet - Twitter thread - Webinar - Zero shot -

Favoris ; AI girls and guys AND Retrieval-based NLP

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63 Documents

LlamaIndex 🦙 sur X : "brand-new course on Building Agentic RAG with LlamaIndex with @DeepLearningAI + @AndrewYNg..."

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2024-05-09 A propos

[2404.13950] SPLATE: Sparse Late Interaction Retrieval

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2024-04-23 A propos

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2024-04-12 A propos

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

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2024-03-30 A propos

DSPy Cheatsheet | DSPy

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2024-03-30 A propos

Nils Reimers sur X : "Embeddings can store only 1 aspect/topic per embedding well."

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2024-03-13 A propos

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

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2024-03-09 A propos

ColBERT gist:c1182551fa609736d47df4af82f7c5ab

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2024-03-08 A propos

ColBERT Inference in the Browser

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2024-03-08 A propos

Jerry Liu sur X : "To better augment LLMs with context, it makes a lot of sense to organize context not just as a flat list of text chunks, but as a hierarchy of high-level to low-level details. RAPTOR..."

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2024-03-03 A propos

Announcing Vespa Long-Context ColBERT | Vespa Blog

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2024-03-03 A propos

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

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DSPy (Demonstrate-Search-Predict)

2024-03-01 A propos

Omar Khattab sur X : "ColBERT in 81 languages by generalizing from English training! ..."

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2024-02-28 A propos

Jerry Liu sur X : "a big step towards better RAG... is to just have a really nice PDF parser. It’s so important because a good parser unlocks way more interesting indexing/retrieval strategies…"

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2024-02-23 A propos

Omar Khattab sur X : "A thread on late interaction, how it works efficiently, and why/where it's been shown to improve quality"

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2024-02-05 A propos

Jerry Liu sur X : "Build a RAG backend over any website in a single CLI command ..."

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2024-02-03 A propos

Craig Macdonald sur X : "a thread of our main ColBERT research findings"

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2024-02-01 A propos

long document ranking · Issue #11 · stanford-futuredata/ColBERT

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2024-01-31 A propos

Exploring ColBERT with RAGatouille | Simon Willison’s TILs

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2024-01-29 A propos

Jo Kristian Bergum sur X : (on "why using ColBERT?")

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2024-01-28 A propos

bclavie/RAGatouille

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2024-01-26 A propos

Jerry Liu sur X : "4 Levels of Agents for RAG..."

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2024-01-23 A propos

LlamaIndex: "Instead of using a global fixed chunk size for RAG, try splitting based on the semantics of the text"

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2024-01-13 A propos

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

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2024-01-01 A propos

Omar Khattab sur X : "A🧵on beating the hardware lottery for retrieval: the internals of the late interaction stack. ColBERT..."

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2023-12-29 A propos

Jerry Liu sur X : "Naive chunking strategies cause poor RAG performance...."

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2023-12-06 A propos

Jerry Liu sur X : "There's different ways you can parse embedded tables for RAG..."

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2023-12-02 A propos

raphaelsty/neural-cherche: Neural Search

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2023-11-17 A propos

Jerry Liu sur X : "Advanced RAG architectures need to implement dynamic retrieval..."

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2023-10-22 A propos

Jerry Liu sur X : "Using LLMs for automated decision making (routing) is a huge part of an advanced RAG/agent app But LLMs are expensive and slow... Fine-tune embeddings instead"

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2023-10-19 A propos

Jerry Liu sur X : "The idea of “small-to-big” retrieval: - retrieve on smaller pieces, expand into more context for LLM synthesis..."

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2023-10-02 A propos

Jerry Liu sur X : "evaluating RAG: purely evaluating retrieval metrics (MRR, precision) isn’t the whole picture - you need end-to-end response evals..."

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2023-09-26 A propos

Omar Khattab sur X : "This isn't the main point of this great new paper by @sophiaalthammer et al. But it's incredible how ColBERT at 1000 training queries is better than DPR trained at *50,000* queries!"

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2023-09-14 A propos

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

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DSPy (Demonstrate-Search-Predict)

2023-09-06 A propos

Jerry Liu sur X : "A simple trick to improve retrieval for RAG 💡: Embed “references” to each text chunk instead of the chunk itself (e.g. smaller chunks, summaries)..."

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2023-09-06 A propos

Jerry Liu sur X : "how do you get a good retrieval dataset w/o spending a ton of money on human labels? Answer: use LLMs"

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2023-08-30 A propos

Jerry Liu sur X : "This might be the first time ChatGPT (+@jxnlco) helped us come up with a better retrieval algorithm for RAG..."

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2023-08-28 A propos

Jerry Liu sur X : "One major way to improve your RAG system is to fine-tune your embedding model"

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2023-08-25 A propos

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

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2023-08-24 A propos

Jerry Liu sur X : "8 key considerations for building *production-grade* LLM apps over your data (RAG)..."

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2023-08-20 A propos

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

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2023-08-17 A propos

Jerry Liu sur Twitter : "Some critical data considerations that you must take into account to make your LLM application production-ready"

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2023-07-23 A propos

Jerry Liu sur Twitter : "Using cross-encoding as a reranking step can dramatically speed up LLM inference time AND improve accuracy!"

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2023-07-20 A propos

Jerry Liu sur Twitter : Hot take: if you want to... deliver technical differentiation, you will need to learn LLM development in a “bottoms-up” fashion

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2023-07-16 A propos

Jerry Liu sur Twitter : "If you’re building “chat over your PDFs” with LLMs, you need to deal with the pesky issue of how to parse embedded tables/diagrams..."

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2023-07-07 A propos

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

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2023-06-23 A propos

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

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2023-06-18 A propos

LangChain Retrieval Webinar - YouTube

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2023-05-27 A propos

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..."

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2023-04-11 A propos

[2304.01982] Rethinking the Role of Token Retrieval in Multi-Vector Retrieval

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2023-04-05 A propos

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

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2023-02-18 A propos

Omar Khattab sur Twitter : "New features in 𝗖𝗼𝗹𝗕𝗘𝗥𝗧 ‣ Index Updater. Simple API to add/remove documents..."

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2023-01-30 A propos

[2208.03299] Few-shot Learning with Retrieval Augmented Language Model

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2022-08-08 A propos

[2207.06300] Re2G: Retrieve, Rerank, Generate

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2022-07-14 A propos

[2203.13088] Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction

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2022-03-30 A propos

[2108.13934] Robust Retrieval Augmented Generation for Zero-shot Slot Filling

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2022-01-19 A propos

Integrate ORQA and REALM for Open Domain Question Answering · Issue #312 · deepset-ai/haystack

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2022-01-12 A propos

[2004.12832] ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

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2022-01-12 A propos

[2007.00814] Relevance-guided Supervision for OpenQA with ColBERT

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2022-01-07 A propos

[2112.01488] ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction

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2021-12-05 A propos

Building Scalable, Explainable, and Adaptive NLP Models with Retrieval | SAIL Blog

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2021-10-07 A propos

A Moderate Proposal for Radically Better AI-powered Web Search

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2021-07-10 A propos

[2012.04584] Distilling Knowledge from Reader to Retriever for Question Answering

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> a method to train an information retrieval module for downstream tasks, **without using pairs of queries and documents as annotations**.

Uses two models (standard pipeline for open-domain QA):

- the first one retrieves documents from a large source of knowledge (the retriever)
- the second one processes the support documents to solve the task (the reader).

> First the retriever selects support passages in a large knowledge
source. Then these passages are processed by the reader, along with the question, to generate an
answer

Inspired by knowledge distillation: the reader model is the teacher and the retriever is the student.

> More precisely, we use a sequence-to-sequence model as the reader, and use
the attention activations over the input documents as synthetic labels to train the retriever. 
> (**train the retriever by learning to approximate the attention score of the reader**)

Refers to:

- [REALM: Retrieval-Augmented Language Model Pre-Training](doc:2020/12/2002_08909_realm_retrieval_a)
- [Dehghani: Neural Ranking Models with Weak Supervision](doc:?uri=https%3A%2F%2Farxiv.org%2Fabs%2F1704.08803)

2020-12-11 A propos