SOTAVerified

Conversational Response Selection

Conversational response selection refers to the task of identifying the most relevant response to a given input sentence from a collection of sentences.

Papers

Showing 110 of 46 papers

TitleStatusHype
Efficient Dynamic Hard Negative Sampling for Dialogue SelectionCode0
P5: Plug-and-Play Persona Prompting for Personalized Response SelectionCode0
Knowledge-aware response selection with semantics underlying multi-turn open-domain conversationsCode0
Dial-MAE: ConTextual Masked Auto-Encoder for Retrieval-based Dialogue SystemsCode0
Learning Dialogue Representations from Consecutive UtterancesCode1
One Agent To Rule Them All: Towards Multi-agent Conversational AICode0
Two-Level Supervised Contrastive Learning for Response Selection in Multi-Turn Dialogue0
Small Changes Make Big Differences: Improving Multi-turn Response Selection in Dialogue Systems via Fine-Grained Contrastive Learning0
Exploring Dense Retrieval for Dialogue Response SelectionCode1
Response Ranking with Multi-types of Deep Interactive Representations in Retrieval-based DialoguesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BERT-FP+EDHNSR10@10.96Unverified
2DialMAER10@10.93Unverified
3BERT-TLR10@10.93Unverified
4BERT-FPR10@10.87Unverified
5BERT-SLR10@10.78Unverified
6UMS_BERT+R10@10.76Unverified
7SA-BERT+HCLR10@10.72Unverified
8SA-BERTR10@10.7Unverified
9IMNR10@10.62Unverified
10U2U-IMNR10@10.62Unverified