TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	REMOVE
Natural Language Inference	V-SNLI	V-BiMPM	Accuracy	86.99	# 1
Natural Language Inference	V-SNLI	BiMPM	Accuracy	86.41	# 2

🦡 Badges

Include the markdown at the top of your GitHub README.md file to showcase the performance of the model.

Badges are live and will be dynamically updated with the latest ranking of this paper.

Badge	Markdown
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/grounded-textual-entailment/natural-language-inference-on-v-snli)](https://paperswithcode.com/sota/natural-language-inference-on-v-snli?p=grounded-textual-entailment)`

Grounded Textual Entailment

COLING 2018 • Hoa Trong Vu • Claudio Greco • Aliia Erofeeva • Somayeh Jafaritazehjan • Guido Linders • Marc Tanti • Alberto Testoni • Raffaella Bernardi • Albert Gatt

Capturing semantic relations between sentences, such as entailment, is a long-standing challenge for computational semantics. Logic-based models analyse entailment in terms of possible worlds (interpretations, or situations) where a premise P entails a hypothesis H iff in all worlds where P is true, H is also true... (read more)