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Description

An advanced End-to-End MLLM is designed to accept various forms of references and effectively ground responses. The Ferret Model utilizes a combination of Hybrid Region Representation and a Spatial-aware Visual Sampler, which allows for detailed and flexible referring and grounding capabilities within the MLLM framework. The GRIT Dataset, comprising approximately 1.1 million entries, serves as a large-scale and hierarchical dataset specifically crafted for robust instruction tuning in the ground-and-refer category. Additionally, the Ferret-Bench is a comprehensive multimodal evaluation benchmark that simultaneously assesses referring, grounding, semantics, knowledge, and reasoning, ensuring a well-rounded evaluation of the model's capabilities. This intricate setup aims to enhance the interaction between language and visual data, paving the way for more intuitive AI systems.

Description

Automating the reference checking process through online systems enables your team to save time, reduce the risk of human errors, and allows references to fill out surveys at their convenience. While finding reliable volunteers may prove challenging, verifying their backgrounds doesn’t have to be. There are candidates who might not align well with your organization’s values, and traditional background checks may overlook this issue. Enhance your organization's security with efficient reference checks that provide an additional safeguard. For a single fee per applicant, you can utilize our automated reference checking software to evaluate up to 50 references. This system facilitates the collection of fast and unbiased feedback from various references for all your candidates. You can distribute standardized reference questionnaires to as many individuals as you wish, making it simple to compile objective evaluations swiftly and efficiently. This streamlined process not only supports better hiring decisions but also fosters a more reliable vetting system.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

$8.95 one-time payment
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apple

Founded

1976

Country

United States

Website

github.com/apple/ml-ferret

Vendor Details

Company Name

Interactive HR

Country

United States

Website

onlinereferencecheck.com

Product Features

Reference Check

Audio References No 
Bulk Reference Request Yes 
Candidate Scoring No 
Completion Alerts No 
Email / Online No 
Mobile Access No 
Reminders No 
Reporting/Analytics No 
Survey Builder Yes 
Survey Library Yes 
Video References No 

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