Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup
The deployment of Large Multimodal Models (LMMs) within AntGroup has significantly
advanced multimodal tasks in payment, security, and advertising, notably enhancing …
advanced multimodal tasks in payment, security, and advertising, notably enhancing …
A Directional Diffusion Graph Transformer for Recommendation
In real-world recommender systems, implicitly collected user feedback, while abundant,
often includes noisy false-positive and false-negative interactions. The possible …
often includes noisy false-positive and false-negative interactions. The possible …
CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion
State-of-the-art pre-trained image models predominantly adopt a two-stage approach: initial
unsupervised pre-training on large-scale datasets followed by task-specific fine-tuning using …
unsupervised pre-training on large-scale datasets followed by task-specific fine-tuning using …
Text2Pic Swift: Enhancing Long-Text to Image Retrieval for Large-Scale Libraries
Text-to-image retrieval plays a crucial role across various applications, including digital
libraries, e-commerce platforms, and multimedia databases, by enabling the search for …
libraries, e-commerce platforms, and multimedia databases, by enabling the search for …
LaCViT: A Label-Aware Contrastive Fine-Tuning Framework for Vision Transformers
Vision Transformers (ViTs) have emerged as popular models in computer vision,
demonstrating state-of-the-art performance across various tasks. This success typically …
demonstrating state-of-the-art performance across various tasks. This success typically …
Large Multimodal Model Compression via Iterative Efficient Pruning and Distillation
The deployment of Large Multimodal Models (LMMs) within Ant Group has significantly
advanced multimodal tasks in payment, security, and advertising, notably enhancing …
advanced multimodal tasks in payment, security, and advertising, notably enhancing …
Multiway-Adapter: Adapting Multimodal Large Language Models for Scalable Image-Text Retrieval
As Multimodal Large Language Models (MLLMs) grow in size, adapting them to specialized
tasks becomes increasingly challenging due to high computational and memory demands …
tasks becomes increasingly challenging due to high computational and memory demands …
Ducho 2.0: Towards a More Up-to-Date Feature Extraction and Processing Framework for Multimodal Recommendation
M Attimonelli, D Danese, D Malitesta, C Pomo… - arXiv preprint arXiv …, 2024 - arxiv.org
In this work, we introduce Ducho 2.0, the latest stable version of our framework. Differently
from Ducho, Ducho 2.0 offers a more personalized user experience with the definition and …
from Ducho, Ducho 2.0 offers a more personalized user experience with the definition and …
Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation
In this work, we introduce Ducho 2.0, the latest stable version of our framework. Differently
from Ducho, Ducho 2.0 offers a more personalized user experience with the definition and …
from Ducho, Ducho 2.0 offers a more personalized user experience with the definition and …
[PDF][PDF] WIP: A First Look At Employing Large Multimodal Models Against Autonomous Vehicle Attacks
As the advent of autonomous vehicle (AV) technology revolutionizes transportation, it
simultaneously introduces new vulnerabilities to cyber-attacks, posing significant challenges …
simultaneously introduces new vulnerabilities to cyber-attacks, posing significant challenges …