Semanlink - NLP tasks / problems ; Knowledge bases AND Information retrieval

Printer friendly

Search Tag:

Search Doc:

Preferences...

Tag Cloud

@jobergum - Arxiv Doc - ColBERT - Discuté avec Raphaël - Domain specific corpora - EMNLP 2021 - Entity linking - Entity Retrieval - ESWC - Gautier Izacard - GitHub project - Hard negative mining - Information retrieval - Knowledge-augmented Language Models - Knowledge distillation - Knowledge Extraction - Knowledge Graphs - Knowledge-Intensive NLP Tasks - Knowledge management - Language Models + Knowledge - Laure Soulier - LLM - LM + Search - Long documents - Lynda Tamine - Michael Glass - Natural language generation - Neural Search - NLP@ENS - NLP@Facebook - NLP@IBM - NLP@Meta - NLP@Stanford - NLP based IR - Not Encoding Factual Knowledge in Language Model - Omar Khattab - Personal assistant - Personal Knowledge Base - Question Answering - Random walk - Retrieval augmented LM - Retriever-Reader - Slides - Slot filling - Thèse IRIT-Renault: biblio initiale - Tutorial - Tweet - Word2vec - Word sense / Lexical ambiguity - Zero shot -

NLP tasks / problems ; Knowledge bases AND Information retrieval

Common descendants

BLINK

21 Documents

raphaelsrty sur X : "My personal Knowledge Base made to the front page of HackerNews today..."

Tags:

2024-03-23 About

Announcing Vespa Long-Context ColBERT | Vespa Blog

Tags:

2024-03-03 About

Ravi Theja sur X : "𝐀𝐜𝐭𝐢𝐯𝐞𝐑𝐀𝐆: 𝐑𝐞𝐯𝐞𝐚𝐥𝐢𝐧𝐠 𝐭𝐡𝐞 𝐓𝐫𝐞𝐚𝐬𝐮𝐫𝐞𝐬 𝐨𝐟 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐯𝐢𝐚 𝐀𝐜𝐭𝐢𝐯𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠..."

Tags:

2024-02-25 About

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

Tags:

2024-01-31 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

[2207.06300] Re2G: Retrieve, Rerank, Generate

Tags:

2022-07-14 About

[2205.00820] Entity-aware Transformers for Entity Search

Tags:

2022-07-12 About

Recent Advances in Retrieval-Augmented Text Generation

Tags:

2022-07-11 About

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

Tags:

2022-01-19 About

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

Tags:

2022-01-12 About

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

Tags:

2021-12-05 About

Linking Entities with Knowledge Graphs | by Sigurd Berglann | Strise | Medium

Tags:

2021-02-05 About

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

Tags:

> 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 About

[1911.03814] Scalable Zero-shot Entity Linking with Dense Entity Retrieval

Tags:

2020-05-02 About

Sebastian Riedel sur Twitter : Happy to introduce BLINK, the @facebookai open-source entity linker!...

Tags:

2020-05-02 About

A Tri-Partite Neural Document Language Model for Semantic Information Retrieval (2018 - ESWC conference)

Tags:

2018-06-08 About

Tutorial on Poincaré Embeddings (Jupyter Notebook )

Tags:

2018-05-20 About

Implementing Poincaré Embeddings | RARE Technologies

Tags:

2018-05-20 About

[1710.04099] Wembedder: Wikidata entity embedding web service

Tags:

2018-02-13 About