Methods › Sequential › Sequence To Sequence Models › ESIM

Enhanced Sequential Inference Model

ESIM

15 papers tagged archive 2025-07-28

Introduced by Qian Chen et al. in Enhanced LSTM for Natural Language Inference

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Enhanced Sequential Inference Model or ESIM is a sequential NLI model proposed in Enhanced LSTM for Natural Language Inference paper.

PaperSource

Papers archive 2025-07-28

15 shown of 15, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Natural Language Inference9
Sentence3
Common Sense Reasoning2
Representation Learning2
Transfer Learning2
Word Embeddings2
Conversational Response Selection1
Descriptive1
Dialogue Evaluation1
Diversity1
Goal-Oriented Dialog1
Language Modelling1
Learning-To-Rank1
Multi-Task Learning1
Multiple-choice1
Open-Domain Dialog1
Recommendation Systems1
Retrieval1
Sequential Recommendation1
model1

Usage over time archive 2025-07-28

Papers per year tagged with ESIM: 2016 to 2024, peak 5 5 0 2016: 2 papers 2016 2017: 1 paper 2017 2018: 5 papers 2018 2019: 4 papers 2019 2020: 2 papers 2020 2021: 0 papers 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (15 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Sequence To Sequence Models

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