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Data · dataset · 2026

Multi-Modal Fusion Prompter Model

Listed in ScienceDB

This dataset contains the PyTorch source code of the MFPM model proposed in the paper "Research on Missing Modal Completion and Dual Branch Dynamic Fusion Sentiment Analysis Model Based on Hint Learning", as well as the raw output results and chart drawing data of all experiments.

Description

The experiment covers four benchmark datasets: CMU-MOSI, CMU-MOSEI, IEMOCAP, and CH-SIMS, including comparative experiments, ablation experiments, robustness testing (with a loss rate of 5%~95%), generalization experiments, and detailed indicators of sensitivity analysis (ACC, F1, MAE, Corr, etc.) in 64 scenarios of complete modality, single modality loss, and bimodal loss.

The data is stored in Excel format for easy reproduction of paper charts and conclusions. 

Links

Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.j00133.0069710 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:earth-environmentalmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:engineeringmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:humanitiesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:life-sciencesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:social-sciencemapping · scidb cnconnector:scidb_cn@1.0.0
descriptionsource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/description
licensesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/rights
publication_datesource · scidb cnconnector:scidb_cn@1.0.0
titlesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/title