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🚀 Open Research Position: Hallucination Detection & Mitigation in Vision-Language Models (VLMs)

We are looking for motivated students to join our research on hallucination detection and mitigation in Visual Question Answering (VQA) models at RIML Lab.

🔍 Project Description
Visual Question Answering (VQA) models generate text-based answers by analyzing an input image and a query. Despite their success, they still suffer from hallucination issues, where responses are incorrect, misleading, or not grounded in the image content.
This research focuses on detecting and mitigating these hallucinations to enhance the reliability and accuracy of VQA models.

đź“„ Relevant Papers
"Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding"
"CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models"
"Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization"

🔹 Must-Have Requirements
- Strong Python programming skills
- Knowledge of deep learning (especially VLMs)
- Hands-on experience with PyTorch
- Ready to start immediately

⏳ Workload
Commitment: At least 20 hours per week


📌 Note: Filling out this form does not guarantee acceptance. Only shortlisted candidates will receive an email notification.

đź“… Application Deadline: March 28, 2025
đź”— Apply here: Google Form

🛑 This position is now closed. Shortlisted candidates have been notified by March 30, 2025. Thank you to everyone who applied! Stay tuned for future opportunities.

đź“§ For inquiries: [email protected]
đź’¬ Telegram: @amirezzati

@RIMLLab
#research_position #ML_research #DeepLearning #VQA



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🚀 Open Research Position: Hallucination Detection & Mitigation in Vision-Language Models (VLMs)

We are looking for motivated students to join our research on hallucination detection and mitigation in Visual Question Answering (VQA) models at RIML Lab.

🔍 Project Description
Visual Question Answering (VQA) models generate text-based answers by analyzing an input image and a query. Despite their success, they still suffer from hallucination issues, where responses are incorrect, misleading, or not grounded in the image content.
This research focuses on detecting and mitigating these hallucinations to enhance the reliability and accuracy of VQA models.

đź“„ Relevant Papers
"Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding"
"CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models"
"Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization"

🔹 Must-Have Requirements
- Strong Python programming skills
- Knowledge of deep learning (especially VLMs)
- Hands-on experience with PyTorch
- Ready to start immediately

⏳ Workload
Commitment: At least 20 hours per week


📌 Note: Filling out this form does not guarantee acceptance. Only shortlisted candidates will receive an email notification.

đź“… Application Deadline: March 28, 2025
đź”— Apply here: Google Form

🛑 This position is now closed. Shortlisted candidates have been notified by March 30, 2025. Thank you to everyone who applied! Stay tuned for future opportunities.

đź“§ For inquiries: [email protected]
đź’¬ Telegram: @amirezzati

@RIMLLab
#research_position #ML_research #DeepLearning #VQA

BY RIML Lab


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Export WhatsApp stickers to Telegram on Android

From the Files app, scroll down to Internal storage, and tap on WhatsApp. Once you’re there, go to Media and then WhatsApp Stickers. Don’t be surprised if you find a large number of files in that folder—it holds your personal collection of stickers and every one you’ve ever received. Even the bad ones.Tap the three dots in the top right corner of your screen to Select all. If you want to trim the fat and grab only the best of the best, this is the perfect time to do so: choose the ones you want to export by long-pressing one file to activate selection mode, and then tapping on the rest. Once you’re done, hit the Share button (that “less than”-like symbol at the top of your screen). If you have a big collection—more than 500 stickers, for example—it’s possible that nothing will happen when you tap the Share button. Be patient—your phone’s just struggling with a heavy load.On the menu that pops from the bottom of the screen, choose Telegram, and then select the chat named Saved messages. This is a chat only you can see, and it will serve as your sticker bank. Unlike WhatsApp, Telegram doesn’t store your favorite stickers in a quick-access reservoir right beside the typing field, but you’ll be able to snatch them out of your Saved messages chat and forward them to any of your Telegram contacts. This also means you won’t have a quick way to save incoming stickers like you did on WhatsApp, so you’ll have to forward them from one chat to the other.

Export WhatsApp stickers to Telegram on iPhone

You can’t. What you can do, though, is use WhatsApp’s and Telegram’s web platforms to transfer stickers. It’s easy, but might take a while.Open WhatsApp in your browser, find a sticker you like in a chat, and right-click on it to save it as an image. The file won’t be a picture, though—it’s a webpage and will have a .webp extension. Don’t be scared, this is the way. Repeat this step to save as many stickers as you want.Then, open Telegram in your browser and go into your Saved messages chat. Just as you’d share a file with a friend, click the Share file button on the bottom left of the chat window (it looks like a dog-eared paper), and select the .webp files you downloaded. Click Open and you’ll see your stickers in your Saved messages chat. This is now your sticker depository. To use them, forward them as you would a message from one chat to the other: by clicking or long-pressing on the sticker, and then choosing Forward.

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