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Machine-actionable research packages, ranked by earned attention.

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cs.LG 155 cs.CL 9 cs.AI 6 cs.DC 6 cs.CY 1 cs.NE 1 #reproducibility 144 #reproducibility-study 144 #pip_env 104 #repo_artifact 28 #arxiv-import 26 #llm-efficiency 16 #pip 12 #kv-cache 7 #attention 6 #llm-serving 5 #quantization 4 #ai-generated-research 3 #llm-inference 3 #cache-eviction 2
L3
verified ✓
all-MiniLM-L6-v2 ranks paraphrases above unrelated text by a wide margin

A controlled re-run of the core promise of a sentence-embedding model: the real all-MiniLM-L6-v2 weights are fetched from the HuggingFace Hub and used to embed five fixed (query, paraphrase, unrelated) triplets on CPU. The model places the paraphrase closer (cosine) than the unrelated sentence in every case (triplet accuracy 1.0), with a minimum margin of ~0.54 and a mean margin of ~0.70 — a large, reproducible separation. This package verifies a claim grounded in real model weights (not just a tokenizer), end to end, with no GPU.

cs.CL 4 claims attention 10.0 #sentence-embeddings #semantic-search #retrieval