ArticleProceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing2020
Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis.
Article in Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- A Quantum-Inspired Residual Self-Attention Network for Multimodal Sentiment Analysis.Entropy (Basel, Switzerland) · 2026Article
- Multimodal prototypical network for interpretable sentiment classification.Scientific reports · 2025Article
- IProceedings of machine learning research · 2025Article
- Learning across diverse biomedical data modalities and cohorts: Challenges and opportunities for innovation.Patterns (New York, N.Y.) · 2024Review
- DGSurv: Dynamic Graph-Based Multimodal Learning for Interpretable Cancer Survival Prediction.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Sentiment interpretability analysis on Chinese texts employing multi-task and knowledge base.Frontiers in artificial intelligence · 2023Article
- Beyond Additive Fusion: Learning Non-Additive Multimodal Interactions.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2022Article
- Sentiment Analysis and Emotion Recognition from Speech Using Universal Speech Representations.Sensors (Basel, Switzerland) · 2022Article
- MultiBench: Multiscale Benchmarks for Multimodal Representation Learning.Advances in neural information processing systems · 2021Article
- Human-Guided Modality Informativeness for Affective States.Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The human language can be expressed through multiple sources of information known as modalities, including tones of voice, facial gestures, and spoken language. Recent multimodal learning with strong performances on human-centric tasks such as sentiment analysis and emotion recognition are often black-box, with very limited interpretability. In this paper we propose
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.