PairDistill Models and datasets of our EMNLP 2024 paper "PairDistill: Pairwise Relevance Distillation for Dense Retrieval" chaoweihuang/PairDistill-colbertv2 0.1B • Updated Nov 28, 2024 • 6 chaoweihuang/PairDistill-dataset Viewer • Updated Nov 28, 2024 • 809k • 21
FactAlign Models and datasets of our EMNLP 2024 paper "FactAlign: Long-form Factuality Alignment of Large Language Models" chaoweihuang/factalign-gemma2-f1_0.75 Viewer • Updated Oct 7, 2024 • 2.56k • 23 chaoweihuang/factalign-phi3-f1_0.7-fg0.5 Viewer • Updated Oct 7, 2024 • 2.33k • 33 chaoweihuang/factalign-llama3-f1_0.8-fg0.5 Viewer • Updated Oct 7, 2024 • 2.33k • 46 • 2 chaoweihuang/FactAlign-LLaMA-3-8B Text Generation • 8B • Updated Oct 7, 2024 • 31 • 1
PairDistill Models and datasets of our EMNLP 2024 paper "PairDistill: Pairwise Relevance Distillation for Dense Retrieval" chaoweihuang/PairDistill-colbertv2 0.1B • Updated Nov 28, 2024 • 6 chaoweihuang/PairDistill-dataset Viewer • Updated Nov 28, 2024 • 809k • 21
FactAlign Models and datasets of our EMNLP 2024 paper "FactAlign: Long-form Factuality Alignment of Large Language Models" chaoweihuang/factalign-gemma2-f1_0.75 Viewer • Updated Oct 7, 2024 • 2.56k • 23 chaoweihuang/factalign-phi3-f1_0.7-fg0.5 Viewer • Updated Oct 7, 2024 • 2.33k • 33 chaoweihuang/factalign-llama3-f1_0.8-fg0.5 Viewer • Updated Oct 7, 2024 • 2.33k • 46 • 2 chaoweihuang/FactAlign-LLaMA-3-8B Text Generation • 8B • Updated Oct 7, 2024 • 31 • 1
