Research desk
The papers behind how we build
An annotated reading list. Every entry is credited to its original authors, with a note on what it changes once the idea meets a real system.
All entries
2 entries
- 2020NeurIPS 2020PublishedCurated
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Pairs a pretrained generator with a neural retriever over an external corpus, so answers can draw on documents that were never in the training data and can be updated by changing the corpus rather than retraining the model.
- 2020EMNLP 2020PublishedCurated
Dense Passage Retrieval for Open-Domain QA
Replaces term matching with a dual-encoder that embeds questions and passages into the same vector space. Relevance becomes a nearest-neighbour lookup, which lets retrieval find passages that share no vocabulary with the question.
Browse by topic
Foundations
The architectures and pre-training results everything else stands on.
3 entries
Retrieval & RAG
Grounding a model in documents you actually own.
5 entries
Reasoning
Getting a model to show its work, and checking the work.
6 entries
Agents & Tool Use
Models that call tools, hold state, and finish multi-step jobs.
8 entries
Adaptation
Changing what a model does without retraining all of it.
4 entries
Alignment
Steering outputs toward what a person would accept.
6 entries
Evaluation
How you know it works before a customer finds out it does not.
11 entries