FAQs related to GSoC

A friend said they expand SPLADE terms into an OpenSearch BM25 text field and it works. We tested it — 0.36 NDCG@10, worse than plain BM25. Here is why, and how to mostly fix it.

SPLADE Into a BM25 Field: The Tokenizer Trap

Inference-free SPLADE nearly matches full SPLADE quality at 13× lower query latency, no GPU needed at query time. Benchmarked against full SPLADE and BM25 on Qdrant and pyserini.

Inference-Free SPLADE: Full Quality, 13× Faster Queries

Vector databases compress text payloads with LZ4 by default. Tokenize the text first and entropy-code the token IDs, and you get ~3x lossless compression, 2.6x what LZ4 manages, using pieces every ML stack already ships.

Tokenization is a Compression Codec Nobody Uses That Way

Search is everywhere and is one of the hardest problems in CS. Here's why I'm obsessed with it.

Why I'm Obsessed With Search

Reflections on a year of growth, travel, and pursuing mastery

2025: Year in Review

I Reverse-Engineered Exa.ai Infrastructure Cost with Napkin Math

Exploring the JSON embeddings to for matching new products with existing ones

All Posts

FAQs related to GSoC