avnlp/llm-blender

LLM-Blender: Ensembling framework that maximizes LLM performance via pairwise ranking. Employs PairRanker to rank candidates and GenFuser to merge outputs, generating superior responses by combining the diverse strengths of multiple open-source models.

30
/ 100
Emerging

The framework integrates with Haystack RAG pipelines via a custom `LLMBlenderRanker` component, enabling ensemble ranking within retrieval-augmented generation workflows. PairRanker uses cross-attention encoders (RoBERTa) to perform all-pairs candidate comparisons and rank outputs, while GenFuser employs seq2seq fusion to synthesize top-K candidates into enhanced final responses. Evaluation on BillSum and MixInstruct datasets with modern models (Llama-3, Mistral-7B, Phi-3) demonstrates measurable improvements in BERTScore, BARTScore, and BLEURT metrics over individual model outputs.

No Package No Dependents
Maintenance 6 / 25
Adoption 7 / 25
Maturity 9 / 25
Community 8 / 25

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Stars

36

Forks

3

Language

Python

License

MIT

Last pushed

Dec 20, 2025

Commits (30d)

0

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