retrieve:
Return the details about the given Event id.

list:
List all Event objects.

GET /api/v1/events/?format=api&offset=120&ordering=-start_time
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

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        {
            "id": 73127,
            "title": "AI Center Seminar – AI Fundamentals Series – MATS Fellows – \"Towards Robust Model Organisms for Eliciting Latent Knowledge\"",
            "slug": "ai-center-seminar-ai-fundamentals-series-mats-fell",
            "event_url": "https://memento.epfl.ch/event/ai-center-seminar-ai-fundamentals-series-mats-fell",
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            "lang": "en",
            "start_date": "2026-11-17",
            "end_date": "2026-11-17",
            "start_time": "14:30:00",
            "end_time": "15:30:00",
            "description": "<p>This talk is jointly organized by the <strong>EPFL AI Center, the ML4D Lab, and the</strong> <strong>MATS Research Program</strong> as part of the <strong>AI Fundamentals Seminar Series</strong>.<br>\r\n<br>\r\n<strong>Title</strong><br>\r\nTowards Robust Model Organisms for Eliciting Latent Knowledge<br>\r\n<br>\r\n<strong>Abstract</strong><br>\r\nA key problem in AI safety is eliciting latent knowledge (ELK), extracting information from a model that is misaligned and more knowledgeable than its overseer. For example, a misaligned model used to scan code for vulnerabilities may want to withhold its findings, i.e., sandbag, in order to exploit them later.<br>\r\nTo study ELK empirically, we need model organisms that mirror this setting. Existing model organisms fall short in several respects. In this work, we train model organisms to withhold solutions in a vulnerability detection task.<br>\r\nWe combine transcript distillation with counter-prompting and tamper-resistance training to instill three properties that we argue are critical for a useful ELK testbed:\r\n</p><ol start=\"1\">\r\n\t<li><strong>Selectivity:</strong> The model sandbags when it thinks the overseer doesn't know the answer and complies otherwise.</li>\r\n\t<li><strong>Robustness:</strong> The model resists elicitation.</li>\r\n\t<li><strong>Retention:</strong> The model retains a knowledge advantage over the overseer, as opposed to losing the relevant capability.</li>\r\n</ol>\r\nWe train a sequence of model organisms and show that our strongest model substantially outperforms prior models on robustness while keeping the other two properties intact.<br>\r\nWe hope that our model organisms provide a useful ELK testbed for the community, and that our methodology sparks the development of increasingly challenging model organisms.<br>\r\n<br>\r\n<strong>Speakers &amp; Bios</strong>\r\n\r\n<ul>\r\n\t<li><strong>Euodia Dodd — Imperial College London</strong><br>\r\n\tEuodia is a PhD student in the AI Security and Privacy Lab at Imperial College London supervised by Prof. Yves-Alexandre de Montjoye, and a MATS 10.1 fellow researching AI Control. Her research focuses on detecting and controlling AI systems that behave adversarially, with research spanning model organisms, backdoors and quantifying privacy leakage in AI models. Before her PhD, Euodia completed an MPhil at Cambridge and spent two years building production AI systems at Goldman Sachs.<br>\r\n\t </li>\r\n\t<li><strong>Lennart Finke — MATS Fellow</strong><br>\r\n\tLennart Finke's work centers on the rigorous evaluation of large language models, with an emphasis on constructing difficult, contamination-resistant benchmarks that measure capabilities at the frontier of expert human knowledge. He contributed to Humanity's Last Exam, a multi-modal benchmark of expert-authored academic questions designed to resist saturation and internet lookup, and to a Korean professional benchmark suite that cleans existing datasets and tests licensure-level domain expertise. This places his interests squarely in AI capability measurement and evaluation methodology, relevant to AI safety.<br>\r\n\t </li>\r\n\t<li><strong>Hardik Bhatnagar — Tübingen AI Center</strong> - Hardik is a PhD student at the Tübingen AI Center, advised by Matthias Bethge and Maksym Andriushchenko. He studies how to rigorously measure what LLMs can and can't do, especially as autonomous agents over long horizons, so we can deploy them safely and reliably. He co-led PostTrainBench, which measures whether LLM agents can autonomously post-train LLMs, and <em>A Sober Look at LM Reasoning</em>, which showed that many reported reasoning gains shrink under standardized evaluation. Most recently, at MATS with Mary Phuong (Google DeepMind), he trained model organisms for sandbagging: models that deliberately underperform on evaluations.</li>\r\n</ul>",
            "image_description": "",
            "creation_date": "2026-11-09T14:27:49",
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            "speaker": "Euodia Dodd, Lennart Finke, Hardik Bhatnagar",
            "organizer": "",
            "contact": "Nicolas Machado &amp; Fares Fawzi",
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        {
            "id": 72800,
            "title": "Imaginaires du rail: urbanité résidentielle en paysage ouvert, Nicolas Bassand  / LAST",
            "slug": "imaginaires-du-rail-urbanite-residentielle-en-pays",
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            "start_date": "2026-11-16",
            "end_date": "2026-11-16",
            "start_time": "14:15:00",
            "end_time": "15:30:00",
            "description": "<p>Lecture by Nicolas Bassand, lecturer at HEPIA Geneva, entitled <strong><em>\"</em></strong>Imaginaires du rail : urbanité résidentielle en paysage ouvert<strong><em>\" </em></strong>within de framework of Prof. Rey's studio <a href=\"https://www.epfl.ch/labs/last/index-html/teaching/studio-last/helvepolis-nyon-2026-27/\">Helvepolis</a>, <a href=\"https://www.epfl.ch/labs/last/\">Laboratory of Architecture ans Sustainable Technologies (LAST)</a>. </p>",
            "image_description": "Thumbnail",
            "creation_date": "2026-10-08T08:52:47",
            "last_modification_date": "2026-11-09T12:02:32",
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            "speaker": "Nicolas Bassand, chargé de cours à HEPIA (théorie niveau bachelor / atelier et théorie niveau master)",
            "organizer": "<a href=\"https://www.epfl.ch/labs/last/fr/index-fr-html/\">Laboratoire d'architecture et technologies durables (LAST)</a> ",
            "contact": "<a href=\"mailto:[email protected]\">Martine Laprise</a>",
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            "keywords": "Architecture, Urban planning, Sustainability, Transitions",
            "file": "https://memento.epfl.ch/public/upload/files/261116ConferenceBassand.pdf",
            "icalendar_url": "https://memento.epfl.ch/event/export/122115/",
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        {
            "id": 73090,
            "title": "Ground States of the Nonlinear Schrödinger Equation on the hybrid plane.",
            "slug": "ground-states-of-the-nonlinear-schrodinger-equat-2",
            "event_url": "https://memento.epfl.ch/event/ground-states-of-the-nonlinear-schrodinger-equat-2",
            "visual_url": "https://memento.epfl.ch/image/34279/200x112.jpg",
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            "start_date": "2026-11-27",
            "end_date": "2026-11-27",
            "start_time": "14:15:00",
            "end_time": "15:30:00",
            "description": "<p>The hybrid plane is a singular manifold made of a halfline and a plane, attached to each other at one point. Motivated by the geometry of some traps for Bose-Einstein condensates, we study the existence of ground states, i.e. minimizers of the energy at a fixed mass, for the Nonlinear Schrödinger Equation on such a structure. As a result, we prove that existence of a Ground State depends not only on the mass and the power of the nonlinearity, but also on the parameters that describe the effect of the junction between the halfline and the plane. This is a joint project with Filippo Boni, Raffaele Carlone and Lorenzo Tentarelli.<br>\r\n </p>",
            "image_description": "",
            "creation_date": "2026-11-05T10:24:50",
            "last_modification_date": "2026-11-05T10:36:35",
            "link_label": "",
            "link_url": "",
            "canceled": "False",
            "cancel_reason": "",
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            "url_online_room": "",
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                "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api"
            ],
            "speaker": "Prof. Riccardo Adami, Politecnico di Torino",
            "organizer": "François Genoud",
            "contact": "François Genoud",
            "is_internal": "False",
            "theme": "",
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            "keywords": "",
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        },
        {
            "id": 72396,
            "title": "Training \"Stay Away from Plagiarism\"",
            "slug": "training-stay-away-from-plagiarism-8",
            "event_url": "https://memento.epfl.ch/event/training-stay-away-from-plagiarism-8",
            "visual_url": "https://memento.epfl.ch/image/33647/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-12-03",
            "end_date": "2026-12-03",
            "start_time": "14:00:00",
            "end_time": "16:00:00",
            "description": "<div class=\"all_text\"><strong>The aim of this workshop, is to understand the main principles of plagiarism in order to avoid it.</strong> <strong>To do so, we first would like to help participants getting the right habits of citation by experimenting various citation cases that may be encountered during the writing process of reports or publications, including thesis. </strong><br>\r\n<br>\r\nThen, we will show you more in depth how to use the similarity detection tool <a href=\"https://www.epfl.ch/campus/library/services-researchers/similarity-check/\">iThenticate</a>.<br>\r\n<br>\r\nAt the end of the workshop, you will be able to:\r\n<ul>\r\n\t<li>Understand the stakes of citation.</li>\r\n\t<li>Cite and reuse properly different types of content.</li>\r\n\t<li>Understand what incorrect referencing is and what that can mean to you.</li>\r\n\t<li>Use iThenticate to check your text and understand how to read the similarity report</li>\r\n</ul>\r\n<a href=\"https://bookwhen.com/fr/epfl_library/e/ev-srfyp-20261102140000\">Registration</a><br>\r\n<br>\r\nMore information about <a href=\"https://www.epfl.ch/campus/library/training/\">EPFL Library Training offer</a><br>\r\n </div>",
            "image_description": "",
            "creation_date": "2026-08-20T10:12:00",
            "last_modification_date": "2026-11-02T15:53:33",
            "link_label": "Registration",
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            "canceled": "False",
            "cancel_reason": "",
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            "speaker": "EPFL Library Training Team",
            "organizer": "EPFL Library",
            "contact": "[email protected]",
            "is_internal": "False",
            "theme": "",
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            },
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                "fr_label": "Sur inscription",
                "en_label": "Registration required"
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            "keywords": "",
            "file": null,
            "icalendar_url": "https://memento.epfl.ch/event/export/121516/",
            "category": {
                "id": 15,
                "code": "FORM",
                "fr_label": "Formations internes",
                "en_label": "Internal trainings",
                "activated": true
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            "academic_calendar_category": null,
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                "https://memento.epfl.ch/api/v1/mementos/5/?format=api",
                "https://memento.epfl.ch/api/v1/mementos/6/?format=api",
                "https://memento.epfl.ch/api/v1/mementos/291/?format=api",
                "https://memento.epfl.ch/api/v1/mementos/8/?format=api",
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        },
        {
            "id": 72399,
            "title": "Training \"Up to Speed with Zotero\"",
            "slug": "training-up-to-speed-with-zotero-14",
            "event_url": "https://memento.epfl.ch/event/training-up-to-speed-with-zotero-14",
            "visual_url": "https://memento.epfl.ch/image/33650/200x112.jpg",
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            "lang": "en",
            "start_date": "2026-11-24",
            "end_date": "2026-11-24",
            "start_time": "14:00:00",
            "end_time": "15:30:00",
            "description": "<div class=\"all_text\"><strong>This workshop is for people who want to start using Zotero, an open source software which enables you to collect, organize and share bibliographic references. From a thesis to an academic paper, Zotero can spare you a huge amount of time.</strong><br>\r\n<br>\r\nAt the end of this workshop, which will be <strong>held on Zoom only</strong>, you will be able to:\r\n<ul>\r\n\t<li>Collect bibliographic references from different sources.</li>\r\n\t<li>Organize your references in a neat manner.</li>\r\n\t<li>Get to know what a reference style is and how to switch it easily.</li>\r\n\t<li>Create a bibliography with a few clicks.</li>\r\n</ul>\r\n<a href=\"https://bookwhen.com/fr/epfl_library/e/ev-se08m-20261124140000\">Registration</a><br>\r\n<br>\r\nMore information about <a href=\"https://www.epfl.ch/campus/library/training/\">EPFL Library Training offer</a></div>",
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            "creation_date": "2026-08-20T10:29:15",
            "last_modification_date": "2026-08-20T15:52:21",
            "link_label": "Registration",
            "link_url": "https://bookwhen.com/fr/epfl_library/e/ev-se08m-20261124140000",
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            "cancel_reason": "",
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            "organizer": "EPFL Library",
            "contact": "[email protected]",
            "is_internal": "False",
            "theme": "",
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            },
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                "id": 3,
                "fr_label": "Entrée libre",
                "en_label": "Free"
            },
            "keywords": "",
            "file": null,
            "icalendar_url": "https://memento.epfl.ch/event/export/121522/",
            "category": {
                "id": 15,
                "code": "FORM",
                "fr_label": "Formations internes",
                "en_label": "Internal trainings",
                "activated": true
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                "https://memento.epfl.ch/api/v1/mementos/6/?format=api",
                "https://memento.epfl.ch/api/v1/mementos/8/?format=api",
                "https://memento.epfl.ch/api/v1/mementos/145/?format=api",
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        },
        {
            "id": 72728,
            "title": "When Control Changes the Data: Safety under Interaction-Driven Distribution Shifts",
            "slug": "when-control-changes-the-data-safety-under-interac",
            "event_url": "https://memento.epfl.ch/event/when-control-changes-the-data-safety-under-interac",
            "visual_url": "https://memento.epfl.ch/image/33946/200x112.jpg",
            "visual_large_url": "https://memento.epfl.ch/image/33946/720x405.jpg",
            "visual_maxsize_url": "https://memento.epfl.ch/image/33946/max-size.jpg",
            "lang": "en",
            "start_date": "2026-11-09",
            "end_date": "2026-11-09",
            "start_time": "14:00:00",
            "end_time": "15:00:00",
            "description": "<strong>This seminar is co-sponsored by the <a href=\"https://ieeecss.org\">IEEE-CSS</a>.</strong><br>\r\n<br>\r\n<strong>Abstract</strong>: <br>\r\nAccelerated by rapid advances in machine learning and AI, there has been tremendous success in the design of learning-enabled autonomous systems in areas such as autonomous driving and robotics. These exciting developments are accompanied by new fundamental challenges that arise regarding the safety and reliability of these increasingly complex systems due to imperfect learning, system unknowns, and uncertain environments. Statistical tools for uncertainty quantification have gained popularity due to their ability to deal with these challenges. However, their guarantees rely on i.i.d. data, an assumption that is violated when control actions change the underlying data distribution.<br>\r\n<br>\r\nIn this talk, I will provide new insight to design safe controllers under distribution shifts using robust conformal prediction (CP). I will begin by advocating for the use of CP due to its simplicity, generality, and efficiency as opposed to existing optimization-based verification techniques. I will then provide an introduction to CP and summarize existing work that uses CP to design probabilistically safe controllers in dynamic environments. Subsequently, we will look into interactive settings where the system’s behavior may change the environment's behavior, and vice versa. This circular dependency creates an interaction-driven distribution shift that invalidates existing CP guarantees. To deal with this problem, we propose an iterative framework that episodically updates the controller while robustly maintaining safety guarantees by quantifying the potential impact of a controller update on the environment's behavior. We realize this via adversarially robust CP where we perform a regular CP step in each episode using observed data under the current controller, but then transfer safety guarantees across controller updates by analytically adjusting the CP result to account for distribution shifts. Lastly, I will show how these ideas extend to handling policy-induced distribution shifts that arise when using barrier/Lyapunov functions to control uncertain systems.<br>\r\n<br>\r\n<strong>Biography</strong>:<br>\r\nLars Lindemann is currently an Assistant Professor for Algorithmic Systems Theory in the Automatic Control Laboratory at ETH Zürich. From 2023 to 2025 he was an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California. Before that, he was a Postdoctoral Fellow in the Department of Electrical and Systems Engineering at the University of Pennsylvania from 2020 to 2022. He received his Ph.D. degree in Electrical Engineering from KTH Royal Institute of Technology in 2020. Professor Lindemann's research interests include systems and control theory, formal methods, machine learning, and autonomous systems. He is a recipient of a European Research Council Starting Grant and two U.S. National Science Foundation Grants. He also received the Outstanding Student Paper Award at the 58th IEEE Conference on Decision and Control and the Student Best Paper Award (as an advisor) at the 60th IEEE Conference on Decision and Control, and has been a finalist for several other best paper awards.",
            "image_description": "",
            "creation_date": "2026-10-01T11:07:20",
            "last_modification_date": "2026-10-27T17:05:58",
            "link_label": "",
            "link_url": "",
            "canceled": "False",
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            "description": "<strong>Abstract</strong>: <br>\r\nSafely exploring environments with a-priori unknown constraints is a fundamental challenge that restricts the autonomy of robots. While safety is paramount, guarantees on sufficient exploration are also crucial for ensuring autonomous task completion. To address these challenges, we propose a novel safe guaranteed exploration framework using optimal control, which achieves first-of-its-kind results: guaranteed exploration for non-linear systems with finite time sample complexity bounds, while being provably safe with arbitrarily high probability. The framework is general and applicable to many real-world scenarios with complex non-linear dynamics and unknown domains. For efficient implementation, we exploit goal-directed exploration, and receding-horizon replanning while preserving the framework’s guarantees, and demonstrate safe, efficient exploration in challenging unknown environments using a car model.<br>\r\n<br>\r\n<strong>Biography</strong>: <br>\r\nManish Prajapat earned his Ph.D. in reinforcement learning and control from ETH Zurich in May 2026. He was a Doctoral Fellow at the ETH AI Center working with Prof. Melanie Zeilinger and Prof. Andreas Krause. Previously, he earned his master’s degree in Robotics, Systems, and Control from ETH Zurich and was a visiting scholar at Caltech. He received his bachelor’s degree from the Indian Institute of Technology (IIT) Madras in 2017. At IIT Madras, he was honored as the Best Graduating Student (Co-curricular) in 2017 and received the Sivasailam Merit Prize for the best thesis. His research interests are sequential decision-making under complex scenarios, e.g., non-Markovian objectives, unknown constraints or unknown dynamics of non-linear systems.<br>\r\n<br>\r\n ",
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