Analyzing Semantic Redundancy in LLM Retrieval (Google GIST Protocol)
Show HN: Analyzing Semantic Redundancy in LLM Retrieval (Google GIST Protocol)
Analyzing Semantic Redundancy in LLM Retrieval (Google GIST Protocol) is a business in show hn launch.
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Last week, Google research published details on GIST (Greedy Independent Set Thresholding), a new protocol presented at NeurIPS 2025. I was fascinated by the paper, so I built a tool to visualize the "No-Go Zones" (redundancy radius) it describes.The Tool: https://websiteaiscore.com/gist-compliance-checkThe Context (The Paper): To understand the tool, you have to understand the problem Google is solving with GIST: redundancy is expensive. When generating an AI answer , the model cannot feed 10k search results into the context window—it costs too much compute. If the top 5 results are semantically identical (consensus content), the model wastes tokens processing duplicates.The GIST algorithm
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Website: websiteaiscore.com/gist-compliance-checkThe
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