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Models/C2CRS

C2CRS

Reported on 6 benchmarks across 2 tasks · 1 paper · 3 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Knowledge Base3 results

Recommendation SystemsonReDial
Recall@1· 2022-01-04
0.053
best: 0.056 (KERL)
SOTA
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System arXiv:2201.02732
Recommendation SystemsonReDial
Recall@10· 2022-01-04
0.233
SOTA
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System arXiv:2201.02732
Recommendation SystemsonReDial
Recall@50· 2022-01-04
0.407
best: 0.428 (UniCRS)
SOTA
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System arXiv:2201.02732

Adversarial3 results

Text GenerationonReDial
Distinct-2· 2022-01-04
0.189
best: 0.492 (UniCRS)
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System arXiv:2201.02732
Text GenerationonReDial
Distinct-3· 2022-01-04
0.334
best: 0.648 (UniCRS)
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System arXiv:2201.02732
Text GenerationonReDial
Distinct-4· 2022-01-04
0.424
best: 0.832 (UniCRS)
C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System arXiv:2201.02732