Overview of phrase retrieval for open-domain QA, using dense-sparse representations to bypass the retriever-reader pipeline.

Solution for the Programmers immigration problem using binary search on time cost.

An approach that enables large-batch contrastive learning under memory constraints by using in-batch negatives instead of explicit negative sampling.

Types of training bias in MRC and ODQA, and techniques to mitigate them including negative sampling and annotation bias handling.

Deep dive into Open Domain Question Answering, covering the Retriever-Reader approach, distant supervision, and passage granularity strategies.

Scaling passage retrieval with approximate similarity search techniques: scalar quantization, inverted file indexing, and FAISS.