Natural Language Inference
Natural Language Inference (NLI) is the task of determining whether a hypothesis is true given a premise, including three types of relationships: entailment, contradiction, and neutral. This task often employs methods such as deep learning, and common datasets used include SNLI, MultiNLI, and SciTail. NLI has significant application value in natural language processing, capable of enhancing machine understanding and reasoning abilities.
SNLI
EFL (Entailment as Few-shot Learner) + RoBERTa-large
RTE
PaLM 540B (fine-tuned)
MultiNLI
T5-11B
QNLI
ALICE
ANLI test
WNLI
DeBERTa
LiDiRus
RCB
TERRa
CommitmentBank
PaLM 540B (finetuned)
SciTail
MT-DNN-SMARTLARGEv0
FarsTail
Translate-Source + fastText
MultiNLI Dev
TinyBERT-6 67M
MedNLI
CharacterBERT (base, medical)
XNLI French
CamemBERT (large)
e-SNLI
ExplainThenPredictAttention (e-InferSent Bi-LSTM + Attention)
V-SNLI
MMBT
XNLI Chinese Dev
ERNIE 2.0 Large
XNLI Chinese
ERNIE 2.0 Large
JamPatoisNLI
AX
BioNLI
BioLinkBert
HANS
Roberta-large
KUAKE-QQR
KUAKE-QTR
MED
NeuralLog
MNLI + SNLI + ANLI + FEVER
MRPC
DeBERTaV3large
Probability words NLI
Quora Question Pairs
SICK
NeuralLog
TabFact
XWINO
mGPT
ANLI
ANLI-r3
GLUE
multi_nli