Haystack
- Improving RAG Retrieval with Auto-Merging (12 Sep 2024)
- Benchmarking Haystack Pipelines for Optimal Performance (24 Jun 2024)
- Extract Metadata from Queries to Improve Retrieval (13 May 2024)
Use LLMs to extract metadata from queries to use as filters that improve retrieval in RAG applications. - Incorporate HyDE into Haystack RAG pipelines (28 Feb 2024)
viterbi
sequence-prediction
retrieval-augmented-generation
RAG
Haystack
scikit-learn
pos-tags
evaluation_metrics
conditional-random-fields
classification
NER
word2vec
word-embeddings
triplet-loss
syntactic-dependencies
sentence-transformers
relationship-extraction
neural-networks
fine-tuning
embeddings
coursera
conference
SyntaxNet
NLTK
LSTM
CRF
wikidata
transformers
tokenization
tf-idf
text-summarisation
semantic-web
semantic-drift
retrieval
resources
reference-post
production
portuguese
political-science
named-entity-recognition
naive-bayes
multi-label-classification
monitoring
mlops
metrics
metadata-extraction
maximum-entropy-markov-models
logistic-regression
llms
language-models
information-extraction
imbalanced_data
hyperparameter-optimization
hidden-markov-models
grid-search
gensim
generative-ai
fasttext
evaluation
document-classification
doc2vec
deployment
dependency-graph
dataset
data-challenge
convolutional-neural-networks
contrastive-learning
books
attention
SPARQL
RNN
PyData
KOVENS
GRU