Mohamed Elhoseiny (@moelhoseiny) 's Twitter Profile
Mohamed Elhoseiny

@moelhoseiny

AI Prof @KAUST_news supporting @KAUSTVisionCAIR lab (hiring!), AI artist; formerly @StanfordGSB Igniter,@facebookai,@Baidu,@Adobe,@RutgersU

ID: 1042555955861286912

linkhttp://www.mohamed-elhoseiny.com calendar_today19-09-2018 23:28:04

423 Tweet

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Mohamed Elhoseiny (@moelhoseiny) 's Twitter Profile Photo

📢 New Paper Alert! 🚀📄 Excited to announce "LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding." 📝Paper: lnkd.in/gHYG3ruX 🧑🏻‍💻Code: lnkd.in/gmxunM2C 🚀Project (Demo): lnkd.in/gqKVq25U

📢 New Paper Alert! 🚀📄 Excited to announce "LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding."

📝Paper: lnkd.in/gHYG3ruX
🧑🏻‍💻Code: lnkd.in/gmxunM2C
🚀Project (Demo): lnkd.in/gqKVq25U
Human Capability Initiative (@hci_ksa) 's Twitter Profile Photo

How can innovation protect our planet and expand human potential? The latest #HCI2025 Perspectives from KAUST explores how AI is helping communities thrive in harmony with nature. #BeyondReadiness #SaudiVision2030

CV4E Workshop @ ECCV (@cv4e_eccv) 's Twitter Profile Photo

We are thrilled to announce that CV for Ecology Workshop is returning for its second year at #ICCV2025 in Honolulu, Hawaii! If your work combines computer vision and ecology, submit a paper and join us! Deadlines: July 4 (Proceedings) / July 22 (Non-Archival)

We are thrilled to announce that CV for Ecology Workshop is returning for its second year at #ICCV2025 in Honolulu, Hawaii! If your work combines computer vision and ecology, submit a paper and join us!

Deadlines:  July 4 (Proceedings) / July 22 (Non-Archival)
Mohamed Elhoseiny (@moelhoseiny) 's Twitter Profile Photo

🚀 Excited to share that 7 papers were accepted to ICCV 2025 main conference! 🎉 Huge congrats to the brilliant students and collaborators 🙌 — more details to follow. 📚✨!

GAMMA UMD (@gammaumd) 's Twitter Profile Photo

(2/n) AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs We introduce the Audio-Visual Trustworthiness Benchmark and CAVPref, a model-agnostic training strategy that boosts AVLLM robustness and comprehension by up to 30.19% across 9 challenging

(2/n)
AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs

We introduce the Audio-Visual Trustworthiness Benchmark and CAVPref, a model-agnostic training strategy that boosts AVLLM robustness and comprehension by up to 30.19% across 9 challenging
Mohamed Elhoseiny (@moelhoseiny) 's Twitter Profile Photo

#ICML2025 XIAOQIAN SHEN and team are presenting LongVU paper at ICML on the 17th this week. The developed mechanism was shown to significantly reduce spatiotemporal redundancy in video LLMs.