We built BSE (Bramble Semantic Engine) – a semantic compressor that transforms natural inputs into low-dimensional structured representations.
It's designed as a preprocessing engine for LLMs, capable of reducing long inputs into compact, logic-preserving forms across:
1. Language
Extracts SVO (Subject, Verb, Object) structure
Captures modifiers: adjectives/adverbs
Restores pronouns from short-term memory
Detects questions
Computes:
Compression Rate (%)
Semantic Loss (%)
Compares sentence compression outputs via SDC:
Subject-Subject, Verb-Verb, Object-Subject similarity
Sentence distance
2. Image
Crops and weights center-priority patches
Converts into 100x100 weighted matrices
Visualizes:
R, G, B Channels
Brightness
3. Audio
Decomposes audio into pitch & intensity across frequency bands
Returns normalized 2D matrices
Visualized as grayscale spectro-patches
Live demo (Gradio): https://huggingface.co/spaces/Sibyl-V/BSE_demo
Feedback welcome on:
Compression logic
Use cases (LLM fine-tuning, retrieval, alignment)
Design of multi-modal structure output
Built in 48 hours by a solo dev & their black nine-tailed fox partner. Let us know what you'd improve — and what scares you.
Comments URL: https://news.ycombinator.com/item?id=43670527
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