Mehak Dhaliwal
@mehakdh1
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CS PhD student @ UCSB Interested in AI for Healthcare, NLP, Fairness, and Robustness mehakd on 🦋
Joined December 2021
⏰ Last 2 days for submission at the AIM-FM Workshop at NeurIPS 2024: “Advancements in Medical Foundation Models: Explainability, Robustness, Security, and Beyond”! 📢 We’re accepting submissions on a wide range of topics related to medical foundation models—covering explainability, robustness, fairness, privacy, generative modeling, multimodality, and more in healthcare. 🌐 For more details on the workshop, visit the website at: 🔗 Submission link: 📅 Submission deadline: Aug 30, 2024, 23:59 UTC-0 #NeurIPS2024 #AIMFM #MedicalAI #FoundationModels
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RT @YaoQin_UCSB: 🚨Only 1 day to go! 🚨 Join us at AIM-FM: Advancements In Medical Foundation Models workshop at NeurIPS 2024! 📅 When: Decemb…
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🤖 We benchmarked 7 LLMs (GPT-3.5, Llama2-7B/70B, Llama3-8B/70B, Alpaca-7B, MedAlpaca-7B) using four prompting strategies (instruction, CoT, RAG, CoT+RAG) on carb estimation with NutriBench and compared their performance with a nutritionist. Surprisingly, we discovered that LLMs significantly outperform a human nutritionist. (🧵 4/4)
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RT @WilliamWangNLP: This is exciting! Two independent groups have now confirmed the presence of self-bias in various tasks performed by lar…
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RT @davlanade: Thank you for the interview @matteo_wong @TheAtlantic , great to hear diverse opinions about the topic @bonadossou @IfeAdeba…
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RT @sarahookr: A wonderful piece which draws on researcher perspectives and communities working on this problem. @davlanade @bonadossou @I…
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RT @andong_1997: 🎉 Thrilled to share my first first-author paper on adversarial transfer learning got accepted at @CVPR ! Feel free to chec…
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RT @AlbalakAlon: {UCSB|AI2|UW|Stanford|MIT|UofT|Vector|Contextual AI} present a survey on🔎Data Selection for LLMs🔍 Training data is a clos…
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RT @m2saxon: In case anyone else is digging through their bookmarks looking for these today, here are the rebuttal guides ;) https://t.co/…
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3. MT detection and multi-way parallelism are promising data filtering techniques for improving multilingual data quality. This is also an important issue for AI researchers and internet content consumers as machine-generated content is ever-increasing.
2. The highly multi-way parallel translations are likely machine translations from English to lower-resource languages with significantly lower translation and content quality
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2. The highly multi-way parallel translations are likely machine translations from English to lower-resource languages with significantly lower translation and content quality
Thank you @julesaroscoe @VICENews for covering our work! Read at Key takeaways- 1. A large portion of the internet is translated to many languages (multi-way parallel), with low-resource languages having significantly more translations
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Thank you @julesaroscoe @VICENews for covering our work! Read at Key takeaways- 1. A large portion of the internet is translated to many languages (multi-way parallel), with low-resource languages having significantly more translations
A “shocking” amount of the internet is machine-translated garbage, particularly in languages spoken in Africa and the Global South, researchers say.
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