@maximek3

RS @ DeepMind

 Oxford, United Kingdom
Joined November 2009
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  • Following558
  • Followers146
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Maxime Kayser retweeted
Cornelius Emde@CorEmde14 Dec 2024
Are you scared users might misappropriate your LLM system? 😱 We were scared too! Now we introduce adversarial certificates on the misuse of LLMs. 🤖 Come and see our poster @solarneurips tomorrow. #NeurIPS2024 #NeurIPS #AI #NLP #LLM #DomainCertification #Shhhhhhhh
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🥳🎉Incredibly happy that our paper received an ✨Outstanding Paper Award✨ at #EMNLP2024! Huge congrats particularly to @maximek3, who did an incredible job! So lucky to have you as my student! Check out our paper below ⬇️
Oana-Maria Camburu@oanacamb29 Oct 2024
🚨🌟Very excited to share our #EMNLP2024 work on XAI for healthcare 🩺 We did a large user study with 💫85 medics💫 to find out how natural language explanations and saliency maps influence clinical decision-making Check out the details below ⬇️ #XAI #Medical #UserStudy
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Are self-rationalizing VLMs helpful in a real-world, safety-critical setting? In our new #EMNLP2024 paper 🩺 we recruited 85 medics 🩻 and made them each collaborate with an AI on 80 X-rays under 4 different XAI scenarios arxiv.org/abs/2410.12284 It turns out that: 🧵 (1/n)
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Huge thanks to @oanacamb @neuralisa @CorEmde @RayscapeAI @UniofOxford
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and of course to Susanne Gaube, Bogdan Bercean, Thomas Lukasiewicz, Alex Novak, Abdala Espinosa, Bartlomiej W. Papiez, and all 85 study participants
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There are openings to come work with us on robots and recovery :)! Apply below or ping me if you are interested about doing applied research around robots :) Great chances to do some research before doing a PhD if you are not sure yet whether research if for you. 🤖🦎
Antoine Cully@CULLYAntoine21 Nov 2022
Hey! I am recruiting ASAP several Research Assistants/PostDocs to work on the DARPA LINC research program! If you have experience with Robotics, Machine Learning and Fast Recovery, including Quality-Diversity algorithms, consider applying. More info here: imperial.ac.uk/jobs/descript…
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✨New Paper✨ at #MICCAI2022🩺 🔎 Explaining Chest X-ray Pathologies in Natural Language arxiv.org/abs/2207.04343 with @CorEmde, @oanacamb, Guy Parsons, @bwpapiez, and Thomas Lukasiewicz @UniofOxford #ML #MedicalImaging #Xray #XAI #NLProc (1/5)

Explaining Chest X-ray Pathologies in Natural Language

Most deep learning algorithms lack explanations for their predictions, which limits their deployment in clinical practice. Approaches to improve explainability, especially in medical imaging, have...

arxiv.org
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🗂 Introducing MIMIC-NLE We investigate this by proposing MIMIC-NLE, a high-quality dataset of 44,935 image-diagnosis-NLE triplets extracted from the radiology reports in MIMIC-CXR. The dataset is available at github.com/maximek3/MIMIC-NL…. (4/5)
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📏 Benchmarking different approaches We adapt several models for this new task and compare their performance using automatic and clinician-based evaluations. The results indicate that this is a promising new direction for explaining automated medical image analysis. (5/5)
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If you are at #ICCV2021, come by our poster and have a chat! We'll be at the poster sessions 1A and 1B - Tuesday 3-4pm BST (10-11am EDT) and Thursday 10-11pm BST (5-6pm EDT). See you there😊
Maxime Kayser@maximek316 Sep 2021
🆕 Paper at #ICCV2021💥 😈e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks (VL-NLE) arxiv.org/abs/2105.03761 with @oanacamb, L. Salewski, @CorEmde, @zeynepakata, and T. Lukasiewicz @UniofOxford @uni_tue #ML #CV #XAI #NLProc (1/6)

e-ViL: A Dataset and Benchmark for Natural Language Explanations...

Recently, there has been an increasing number of efforts to introduce models capable of generating natural language explanations (NLEs) for their predictions on vision-language (VL) tasks. Such...

arxiv.org
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