Conversational Response Selection On E

Metrics

R10@1

R10@2

R10@5

Results

Performance results of various models on this benchmark

				Paper Title
BERT-FP+EDHNS	0.957	0.986	0.997	Efficient Dynamic Hard Negative Sampling for Dialogue Selection
DialMAE	0.930	0.977	0.997	Dial-MAE: ConTextual Masked Auto-Encoder for Retrieval-based Dialogue Systems
BERT-TL	0.927	0.974	0.997	Two-Level Supervised Contrastive Learning for Response Selection in Multi-Turn Dialogue
BERT-FP	0.870	0.956	0.993	Fine-grained Post-training for Improving Retrieval-based Dialogue Systems
BERT-SL	0.776	0.919	0.991	Learning an Effective Context-Response Matching Model with Self-Supervised Tasks for Retrieval-based Dialogues
UMS_BERT+	0.762	0.905	0.986	Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection
SA-BERT+HCL	0.721	0.896	0.993	Dialogue Response Selection with Hierarchical Curriculum Learning
SA-BERT	0.704	0.879	0.985	Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots
IMN	0.621	0.797	0.964	Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
U2U-IMN	0.616	0.806	0.966	Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
G-MSN	0.613	0.786	0.964	The World is Not Binary: Learning to Rank with Grayscale Data for Dialogue Response Selection
MSN	0.606	0.770	0.937	Multi-hop Selector Network for Multi-turn Response Selection in Retrieval-based Chatbots
IOI	0.563	0.768	0.950	One Time of Interaction May Not Be Enough: Go Deep with an Interaction-over-Interaction Network for Response Selection in Dialogues
DUA	0.501	0.700	0.921	Modeling Multi-turn Conversation with Deep Utterance Aggregation
SMN	0.453	0.654	0.886	Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots

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Conversational Response Selection On E | SOTA | HyperAI