Full Model

"Full Model" research encompasses the development and improvement of large-scale machine learning models across diverse applications, aiming to enhance performance, efficiency, and robustness. Current research focuses on addressing model vulnerabilities (e.g., adversarial attacks, hallucinations), improving efficiency for resource-constrained devices, and developing specialized models for specific domains (e.g., finance, astronomy, medical imaging). This work is significant for advancing AI capabilities in various fields and for mitigating potential risks associated with deploying complex models in real-world settings.

Papers

November 26, 2024

HyperSeg: Towards Universal Visual Segmentation with Large Language Model
Cong Wei, Yujie Zhong, Haoxian Tan, Yong Liu, Zheng Zhao, Jie Hu, Yujiu Yang
Full Model Image Segmentation Large Language Universal Image Fine Grained Visual Reasoning Segmentation unIvErsal Segmentation
What's in the Image? A Deep-Dive into the Vision of Vision Language Models
Omri Kaduri, Shai Bagon, Tali Dekel
Vision Language Model Full Model Vision Language Vision Paper Deep Dive Visual Complexity
DiffSLT: Enhancing Diversity in Sign Language Translation via Diffusion Model
JiHwan Moon, Jihoon Park, Jungeun Kim, Jongseong Bae, Hyeongwoo Jeon, Ha Young Kim
Full Model Diffusion Explainer Diversity Awareness Sign Language Sign Language Translation Sign Language Video End to End Sign Language
An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models
Yunzhe Hu, Difan Zou, Dong Xu
Deep Neural Network Strong Generalization Full Model Transformer Based Rate Reduction Modern Neural Network Architecture
Safe to Serve: Aligning Instruction-Tuned Models for Safety and Helpfulness
Avinash Amballa, Durga Sandeep Saluru, Gayathri Akkinapalli, Abhishek Sureddy, Akshay Kumar Sureddy
Large Language Model Language Model Full Model Alignment Problem Human SAFETY Unsafe Prompt Helpfulness Score Multi Attribute Helpfulness Dataset
On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidance
Zhixiong Nan, Yilong Chen, Tianfei Zhou, Tao Xiang
Full Model Object Detection Robust Guidance Importance Estimation
ThreatModeling-LLM: Automating Threat Modeling using Large Language Models for Banking System
Shuiqiao Yang, Tingmin Wu, Shigang Liu, David Nguyen, Seung Jang, Alsharif Abuadbba
Full Model Large Language Threat Model Threat Detection

November 25, 2024

Human-Calibrated Automated Testing and Validation of Generative Language Models
Agus Sudjianto, Aijun Zhang, Srinivas Neppalli, Tarun Joshi, Michal Malohlava
Full Model Retrieval Augmented Generation Generative Language Model Human Evaluation External Validation Automated Software Testing Generative Grammar Embedding Based Metric
Towards Efficient Model-Heterogeneity Federated Learning for Large Models
Ruofan Jia, Weiying Xie, Jie Lei, Haonan Qin, Jitao Ma, Leyuan Fang
Full Model Parameter Efficient Fine Tuning Large Model Diverse Model Fine Tuning Task
BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching
Yilong Zhao, Shuo Yang, Kan Zhu, Lianmin Zheng, Baris Kasikci, Yang Zhou, Jiarong Xing, Ion Stoica
Full Model Efficient Inference Worst Case User Throughput Synthetic Multi Modal Dataset Prefix to Prefix Batch Inference Large Auto Regressive Model

November 24, 2024

A Training-Free Approach for Music Style Transfer with Latent Diffusion Models
Sooyoung Kim, Joonwoo Kwon, Heehwan Wang, Shinjae Yoo, Yuewei Lin, Jiook Cha
Full Model Style Transfer Music Generation Training Free Latent Diffusion Playlist Generation
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models
Kexin Zhang, Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Kaize Ding, Xiuqiang He, Xue Liu
Full Model Hybrid Fusion Click Through Rate Prediction Click Through Rate Fusion Strategy

November 23, 2024

November 21, 2024

The importance of the clustering model to detect new types of intrusion in data traffic
Noor Saud Abd, Kamel Karoui
Full Model Importance Aware K Mean Intrusion Detection Network Traffic State of the Art Clustering
Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models
Houze Liu, Tong Zhou, Yanlin Xiang, Aoran Shen, Jiacheng Hu, Junliang Du
Deep Learning Diffusion Model Full Model Medical Image Segmentation Diffusion Explainer Segmentation Network Medical Image Datasets Segmentation Accuracy

Full Model

Papers

HyperSeg: Towards Universal Visual Segmentation with Large Language Model

What's in the Image? A Deep-Dive into the Vision of Vision Language Models

DiffSLT: Enhancing Diversity in Sign Language Translation via Diffusion Model

An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models

Safe to Serve: Aligning Instruction-Tuned Models for Safety and Helpfulness

On-Road Object Importance Estimation: A New Dataset and A Model with Multi-Fold Top-Down Guidance

ThreatModeling-LLM: Automating Threat Modeling using Large Language Models for Banking System

Human-Calibrated Automated Testing and Validation of Generative Language Models

Towards Efficient Model-Heterogeneity Federated Learning for Large Models

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching

A Training-Free Approach for Music Style Transfer with Latent Diffusion Models

Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models

Enabling Efficient Serverless Inference Serving for LLM (Large Language Model) in the Cloud

Machine-agnostic Automated Lumbar MRI Segmentation using a Cascaded Model Based on Generative Neurons

MolMetaLM: a Physicochemical Knowledge-Guided Molecular Meta Language Model

Exploiting Watermark-Based Defense Mechanisms in Text-to-Image Diffusion Models for Unauthorized Data Usage

DyCoke: Dynamic Compression of Tokens for Fast Video Large Language Models

Large Multi-modal Models Can Interpret Features in Large Multi-modal Models

The importance of the clustering model to detect new types of intrusion in data traffic

Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models