Add first retrieval documentation. (#3117)

Adds a file for documenting research in the retrieval direction.

docs/docs/research/retrieval.md

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+# Retrieval Directions and Research Papers
+
+## 1. Retrieval-Index
+
+At first, either a rule-based search a fixed encoder for sematic vector-based
+retrieval (e.g. BERT, Contriever) could be used.
+
+### Relevant Papers
+
+1. FAISS: [https://arxiv.org/abs/1702.08734](https://arxiv.org/abs/1702.08734) -
+   vector index by Facebook
+2. SCaNN: [https://arxiv.org/abs/1908.10396](https://arxiv.org/abs/1908.10396) -
+   vector index by Google
+3. BEIR:
+   [https://arxiv.org/abs/2104.08663v4](https://arxiv.org/abs/2104.08663v4) -
+   Benchmark for Information Retrieval
+4. MS MARCO
+   [https://arxiv.org/abs/1611.09268v3](https://arxiv.org/abs/1611.09268v3) -
+   Machine Reading Comprehension Dataset / Retrieval Benchmark
+
+### Links
+
+- ElasticSearch:
+  [https://www.elastic.co/elasticsearch](https://www.elastic.co/elasticsearch)
+- Apache Lucene: [https://lucene.apache.org/](https://lucene.apache.org/)
+- Meta Faiss:
+  [https://github.com/facebookresearch/faiss](https://github.com/facebookresearch/faiss)
+- Google Scann:
+  [https://github.com/google-research/google-research/tree/master/scann](https://github.com/google-research/google-research/tree/master/scann)
+- Qdrant Vector DB:
+  [https://github.com/qdrant/qdrant](https://github.com/qdrant/qdrant)
+- Milvus Vector DB: [https://milvus.io/](https://milvus.io/)
+- Open Retrieval Index Code:
+  [https://github.com/kenhktsui/open-information-retrieval](https://github.com/kenhktsui/open-information-retrieval)
+
+## 2. Plugin-based approach
+
+In this approach, the retrieval is used on top of a language model. It acts as
+an additional tool, like a search engine for a human.
+
+### Links
+
+- LangChain:
+  [https://github.com/hwchase17/langchain](https://github.com/hwchase17/langchain) -
+  Plugins around any language model
+- LlamaIndex:
+  [https://github.com/jerryjliu/llama_index](https://github.com/jerryjliu/llama_index) -
+  General Retrieval System for LMs and external data
+- LlamaHub: [https://llamahub.ai/](https://llamahub.ai/) - Data Source Plugins
+  for LlamaIndex
+
+### Relevant Papers
+
+- Toolformer: [http://arxiv.org/abs/2302.04761](http://arxiv.org/abs/2302.04761)
+- ...
+
+## 3. Embedding-based approach
+
+The embedding-based approach ingests retrieved information directly into the
+model, e.g. via an additional encoder and cross-attention.
+
+### Relevant papers
+
+- RETRO: [http://arxiv.org/abs/2112.04426](http://arxiv.org/abs/2112.04426)
+- ...