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Found 12 papers, 5 papers with code
Enhancing Cross-Category Learning in Recommendation Systems with Multi-Layer Embedding Training
At constant model quality, MLET allows embedding dimension, and model size, reduction by up to 16x, and 5. 8x on average, across the models.
MusiLingo: Bridging Music and Text with Pre-trained Language Models for Music Captioning and Query Response
Large Language Models (LLMs) have shown immense potential in multimodal applications, yet the convergence of textual and musical domains remains not well-explored.
Mixed-Precision Quantization with Cross-Layer Dependencies
Quantization assigning the same bit-width to all layers leads to large accuracy degradation at low precision and is wasteful at high precision settings.
Factorized Contrastive Learning: Going Beyond Multi-view Redundancy
How can we learn self-supervised multimodal representations to capture both shared and unique information relevant to downstream tasks?
Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
The recent explosion of interest in multimodal applications has resulted in a wide selection of datasets and methods for representing and integrating information from different modalities.
MultiViz: Towards Visualizing and Understanding Multimodal Models
How can we visualize the internal modeling of multimodal interactions in these models?
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations
The ability for a human to understand an Artificial Intelligence (AI) model's decision-making process is critical in enabling stakeholders to visualize model behavior, perform model debugging, promote trust in AI models, and assist in collaborative human-AI decision-making.
Cryo-shift: Reducing domain shift in cryo-electron subtomograms with unsupervised domain adaptation and randomization
Cryo-Electron Tomography (cryo-ET) is a 3D imaging technology that enables the visualization of subcellular structures in situ at near-atomic resolution.
Variability-Aware Training and Self-Tuning of Highly Quantized DNNs for Analog PIM
DNNs deployed on analog processing in memory (PIM) architectures are subject to fabrication-time variability.
Provable hierarchical lifelong learning with a sketch-based modular architecture
We propose a modular architecture for lifelong learning of hierarchically structured tasks.
Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions
Many reinforcement learning (RL) environments in practice feature enormous state spaces that may be described compactly by a "factored" structure, that may be modeled by Factored Markov Decision Processes (FMDPs).
Training with Multi-Layer Embeddings for Model Reduction
Increasing the dimension of embedding vectors improves model accuracy but comes at a high cost to model size.
