HyperAI초신경

홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 컨퍼런스 백과사전 SOTA LLM 모델

한국어

HyperAI초신경

Conversational Response Selection On Douban 1

평가 지표

MAP

MRR

P@1

R10@1

R10@2

R10@5

평가 결과

이 벤치마크에서 각 모델의 성능 결과

비교 표

모델 이름	MAP	MRR	P@1	R10@1	R10@2	R10@5
190501969	0.608	0.650	0.475	0.299	0.494	0.822
modeling-multi-turn-conversation-with-deep	0.551	0.599	0.421	0.243	0.421	0.780
interactive-matching-network-for-multi-turn	0.570	0.615	0.433	0.262	0.452	0.789
fine-grained-post-training-for-improving	0.644	0.680	0.512	0.324	0.542	0.870
domain-adaptive-training-bert-for-response	0.591	0.633	0.454	0.280	0.470	0.828
sequential-matching-network-a-new	0.529	0.569	0.397	0.233	0.396	0.724
knowledge-aware-response-selection-with	0.640	0.678	0.511	0.330	0.520	0.870
dialogue-response-selection-with-hierarchical	0.639	0.681	0.514	0.330	0.531	0.858
do-response-selection-models-really-know-what	0.625	0.664	0.499	0.318	0.482	0.858
speaker-aware-bert-for-multi-turn-response	0.619	0.659	0.496	0.313	0.481	0.847
one-time-of-interaction-may-not-be-enough-go	0.573	0.621	0.444	0.269	0.451	0.786
multi-hop-selector-network-for-multi-turn	0.587	0.632	0.470	0.295	0.452	0.788
knowledge-aware-response-selection-with	0.651	0.687	0.510	0.328	0.552	0.877
global-selector-a-new-benchmark-dataset-and	0.622	0.662	0.481	0.303	0.514	0.852
multi-turn-response-selection-for-chatbots	0.550	0.601	0.427	0.254	0.410	0.757
global-selector-a-new-benchmark-dataset-and	0.648	0.688	0.518	0.327	0.557	0.865