Question Answering On Wikiqa

评估指标

MAP

MRR

评测结果

各个模型在此基准测试上的表现结果

			Paper Title	Repository
TANDA-DeBERTa-V3-Large + ALL	0.927	0.939	Structural Self-Supervised Objectives for Transformers
RLAS-BIABC	0.924	0.908	RLAS-BIABC: A Reinforcement Learning-Based Answer Selection Using the BERT Model Boosted by an Improved ABC Algorithm	-
TANDA-RoBERTa (ASNQ, WikiQA)	0.920	0.933	TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection
DeBERTa-V3-Large + ALL	0.909	0.920	Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection	-
DeBERTa-Large + SSP	0.901	0.914	Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection	-
RoBERTa-Base + SSP	0.887	0.899	Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection	-
RoBERTa-Base Joint MSPP	0.887	0.900	Paragraph-based Transformer Pre-training for Multi-Sentence Inference
Comp-Clip + LM + LC	0.764	0.784	A Compare-Aggregate Model with Latent Clustering for Answer Selection	-
RE2	0.7452	0.7618	Simple and Effective Text Matching with Richer Alignment Features
HyperQA	0.712	0.727	Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering
PWIM	0.7090	0.7234	-	-
Key-Value Memory Network	0.7069	0.7265	Key-Value Memory Networks for Directly Reading Documents
LDC	0.7058	0.7226	Sentence Similarity Learning by Lexical Decomposition and Composition
PairwiseRank + Multi-Perspective CNN	0.7010	0.7180	Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency	-
AP-CNN	0.6886	0.6957	Attentive Pooling Networks
Attentive LSTM	0.6886	0.7069	Neural Variational Inference for Text Processing
LSTM (lexical overlap + dist output)	0.682	0.6988	Neural Variational Inference for Text Processing
MMA-NSE attention	0.6811	0.6993	Neural Semantic Encoders
SWEM-concat	0.6788	0.6908	Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
LSTM	0.6552	0.6747	Neural Variational Inference for Text Processing

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