Methods › Sequential › Sequence To Sequence Models › HBMP

Hierarchical BiLSTM Max Pooling

HBMP

3 papers tagged archive 2025-07-28

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

HBMP is a hierarchy-like structure of BiLSTM layers with max pooling. All in all, this model improves the previous state of the art for SciTail and achieves strong results for the SNLI and MultiNLI.

Source: Sentence Embeddings in NLI with Iterative Refinement Encoders

Papers archive 2025-07-28

3 shown of 3, 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

11 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 Inference2
Autonomous Driving1
Decision Making1
Motion Planning1
Multiple-choice1
Reinforcement Learning (RL)1
Sentence1
Sentence Embedding1
Sentence Embeddings1
Sentence-Embedding1
Transfer Learning1

Usage over time archive 2025-07-28

Papers per year tagged with HBMP: 2018 to 2020, peak 2 2 0 2018: 1 paper 2018 2019: 0 papers 2019 2020: 2 papers 2020
Papers per year the archive tags with this method, by the paper's archive date (3 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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