repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 4d ago
bitsandbytes-foundation/bitsandbytes
Accessible large language models via k-bit quantization for PyTorch.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 53%QuantBench →
- PossiblePossibly related (embedding) · 52%GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache →
- PossiblePossibly related (embedding) · 51%Transformer →
- PossiblePossibly related (embedding) · 50%RaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM Inference →
- PossiblePossibly related (embedding) · 54%The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs →
- PossiblePossibly related (embedding) · 46%Tokenizer Transplantation: Mitigating Autoregressive Collapse in Edge-Efficient Bengali ASR →
- PossiblePossibly related (embedding) · 35%$\text{Log}_\text{b}$Quant: Quantizing Language Models in Logarithmic Space →
“Possibly related via embedding similarity 0.68 (not asserted). Timestamp check: artifact after paper (+6d).”
- PossiblePossibly related (embedding) · 27%BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression →
“Possibly related via embedding similarity 0.59 (not asserted). Timestamp check: artifact slightly before paper (-2d).”
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Related across the graph
paperBiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compressionglossary_termTransformernews[R] Statistically-Lossless Quantization of Large Language ModelspaperThe Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMsnews[Paper] Statistically-Lossless Quantization of Large Language ModelspaperGSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV CachepaperRaBitQCache: Rotated Binary Quantization for KVCache in Long Context LLM InferencetoolQuantBenchpaper$\text{Log}_\text{b}$Quant: Quantizing Language Models in Logarithmic SpacepaperTokenizer Transplantation: Mitigating Autoregressive Collapse in Edge-Efficient Bengali ASR