AlignMamba-2: Enhancing Multimodal Fusion and Sentiment Analysis with Modality-Aware Mamba
AlignMamba-2: Enhancing Multimodal Fusion and Sentiment Analysis with Modality-Aware Mamba explores A multimodal fusion framework leveraging modality-aware Mamba layers to achieve state-of-the-art sentiment analysis with improved efficiency.. Commercial viability score: 7/10 in Multimodal AI.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisTri-Subspaces Disentanglement for Multimodal Sentiment AnalysisViability: 5.0
- Builds On ThisFrom Consistency to Complementarity: Aligned and Disentangled Multi-modal Learning for Time Series Understanding and ReasoningViability: 5.0
- Builds On ThisMamba-3: Improved Sequence Modeling using State Space PrinciplesViability: 4.0
- Builds On ThisTeam LEYA in 10th ABAW Competition: Multimodal Ambivalence/Hesitancy Recognition ApproachViability: 4.0
- Prior WorkVADMamba++: Efficient Video Anomaly Detection via Hybrid Modeling in Grayscale Space