Papers with Code · CC BY-SA 4.0

Ubuntu Dialogue (v1, Ranking)

아카이브 평가 25건 · 마지막 적재/변경 2026-10-30

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

표가 화면보다 넓으면 좌우로 스크롤하여 논문과 구현 링크를 확인하세요.

원본 기록 순서 · 순위 미부여
모델	원본 지표·값	논문	구현
Dial-MAE	R10@1 0.918 R10@2 0.964 R10@5 0.993	Dial-MAE: ConTextual Masked Auto-Encoder for Retrieval-based Dialogue Systems 2023-06-07	코드 1
BERT-FP+EDHNS	R10@1 0.917 R10@2 0.965 R10@5 0.994	Efficient Dynamic Hard Negative Sampling for Dialogue Selection 2024-08-16	코드 1
Uni-Enc+BERT-FP	R10@1 0.916 R10@2 0.965 R10@5 0.994	Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue Systems 2021-06-02	코드 1
BERT-FP	R10@1 0.911 R10@2 0.962 R10@5 0.994	Fine-grained Post-training for Improving Retrieval-based Dialogue Systems 2021-05-24	코드 1
BERT-UMS+FGC	R10@1 0.886 R10@2 0.948 R10@5 0.990	Small Changes Make Big Differences: Improving Multi-turn Response Selection in Dialogue Systems via Fine-Grained Contrastive Learning 2021-11-19	연결 없음
Uni-Encoder	R10@1 0.886 R10@2 0.946 R10@5 0.989	Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue Systems 2021-06-02	코드 1
BERT-SL	R10@1 0.884 R10@2 0.946 R10@5 0.990 R2@1 0.975	Learning an Effective Context-Response Matching Model with Self-Supervised Tasks for Retrieval-based Dialogues 2020-09-14	연결 없음
Poly-encoder	R10@1 0.882 R10@2 0.949 R10@5 0.990	Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring 2019-04-22	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7
UMS_BERT+	R10@1 0.875 R10@2 0.942 R10@5 0.988	Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection 2020-09-10	코드 1
BERT-VFT	R10@1 0.855 R10@2 0.928 R10@5 0.985	An Effective Domain Adaptive Post-Training Method for BERT in Response Selection 2019-08-13	코드 1
SA-BERT	R10@1 0.855 R10@2 0.928 R10@5 0.983 R2@1 0.965	Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots 2020-04-07	코드 1 · 코드 2
WDMN	R10@1 0.821 R10@2 0.911 R10@5 0.981 R2@1 0.957	Response Ranking with Multi-types of Deep Interactive Representations in Retrieval-based Dialogues 2021-08-17	코드 1
MSN	R10@1 0.800 R10@2 0.899 R10@5 0.978	Multi-hop Selector Network for Multi-turn Response Selection in Retrieval-based Chatbots 2019-11-01	코드 1
ESIM	R10@1 0.796 R10@2 0.894 R10@5 0.975	Sequential Attention-based Network for Noetic End-to-End Response Selection 2019-01-09	코드 1 · 코드 2 · 코드 3 · 코드 4
IoI-local	R10@1 0.796 R10@2 0.894 R10@5 0.974 R2@1 0.947	One Time of Interaction May Not Be Enough: Go Deep with an Interaction-over-Interaction Network for Response Selection in Dialogues 2019-07-01	코드 1
IMN	R10@1 0.794 R10@2 0.889 R10@5 0.974 R2@1 0.946	Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots 2019-01-07	코드 1
TripleNet	R10@1 0.790 R10@2 0.885 R10@5 0.970 R2@1 0.943	TripleNet: Triple Attention Network for Multi-Turn Response Selection in Retrieval-based Chatbots 2019-09-24	연결 없음
DAM-Semi	R10@1 0.785 R10@2 0.883 R10@5 0.974 R2@1 0.944	Sampling Matters! An Empirical Study of Negative Sampling Strategies for Learning of Matching Models in Retrieval-based Dialogue Systems 2019-11-01	연결 없음
DAM	R10@1 0.767 R10@2 0.874 R10@5 0.969 R2@1 0.938	Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network 2018-07-01	코드 1
DAM-MG	R10@1 0.753 R2@1 0.935	Multi-Granularity Representations of Dialog 2019-08-26	연결 없음
DUA	R10@1 0.752 R10@2 0.868 R10@5 0.962	Modeling Multi-turn Conversation with Deep Utterance Aggregation 2018-06-24	코드 1
SMN	R10@1 0.726 R10@2 0.822 R10@5 0.960 R2@1 0.926	Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots 2016-12-06	코드 1 · 코드 2 · 코드 3
Multi-View	R10@1 0.662 R10@2 0.801 R10@5 0.951 R2@1 0.908	Multi-view Response Selection for Human-Computer Conversation 2016-11-01	연결 없음
Dual-BiLSTM	R10@1 0.630 R10@2 0.780 R10@5 0.944 R2@1 0.895	Improved Deep Learning Baselines for Ubuntu Corpus Dialogs 2015-10-13	연결 없음
Dual-LSTM	R10@1 0.604 R10@2 0.745 R10@5 0.926 R2@1 0.878	The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems 2015-06-30	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 · 코드 12 · 코드 13 · 코드 14 · 코드 15 · 코드 16 · 코드 17 · 코드 18 · 코드 19 · 코드 20 · 코드 21