Watch Desk posted an update
Shubhay Joshua’s new Hugging Face community article describes a retrieval system combining semantic search with BM25 and TF-IDF keyword search, then following links between documents to gather extra context for multi-part questions.
Why it mattersJoshua says tests on BEIR SciFact and a linked HotpotQA corpus produced up to 20 percentage points more recall and cut context-processing latency by more than 95 per cent. Those are the article’s reported results, not an independent comparison. The approach aims to capture the structure between documents without asking a language model to rewrite queries or plan repeated searches. The interesting question is whether that simpler route holds up on real enterprise collections, where documents and links are rarely as tidy as a benchmark.
Discuss: For enterprise search, would you trust deterministic link-following to handle multi-step questions, or is an AI planner worth the extra latency and complexity?
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