Conversational Response Selection
31 papers with code • 13 benchmarks • 11 datasets
Conversational response selection refers to the task of identifying the most relevant response to a given input sentence from a collection of sentences.
Benchmarks
These leaderboards are used to track progress in Conversational Response Selection
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Libraries
Use these libraries to find Conversational Response Selection models and implementationsDatasets
Reddit
Douban
UDC
DSTC7 Task 1
Reddit Corpus
Advising Corpus
Most implemented papers
Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network
Human generates responses relying on semantic and functional dependencies, including coreference relation, among dialogue elements and their context.
Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots
In this paper, we study the problem of employing pre-trained language models for multi-turn response selection in retrieval-based chatbots.
Dialogue Response Ranking Training with Large-Scale Human Feedback Data
golsun/dialogrpt
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EMNLP 2020
Particularly, our ranker outperforms the conventional dialog perplexity baseline with a large margin on predicting Reddit feedback.
Modeling Multi-turn Conversation with Deep Utterance Aggregation
In this paper, we formulate previous utterances into context using a proposed deep utterance aggregation model to form a fine-grained context representation.
Building Sequential Inference Models for End-to-End Response Selection
JasonForJoy/DSTC7-ResponseSelection
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This paper presents an end-to-end response selection model for Track 1 of the 7th Dialogue System Technology Challenges (DSTC7).
Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
JasonForJoy/IMN
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In this paper, we propose an interactive matching network (IMN) for the multi-turn response selection task.
One Time of Interaction May Not Be Enough: Go Deep with an Interaction-over-Interaction Network for Response Selection in Dialogues
Currently, researchers have paid great attention to retrieval-based dialogues in open-domain.
An Effective Domain Adaptive Post-Training Method for BERT in Response Selection
We focus on multi-turn response selection in a retrieval-based dialog system.
Multi-hop Selector Network for Multi-turn Response Selection in Retrieval-based Chatbots
chunyuanY/Dialogue
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IJCNLP 2019
Existing works mainly focus on matching candidate responses with every context utterance on multiple levels of granularity, which ignore the side effect of using excessive context information.
Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots
The distances between context and response utterances are employed as a prior component when calculating the attention weights.
