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Many high-stakes AI deployments proceed only if every stakeholder deems the system acceptable relative to their own minimum standard. With randomization over a finite menu of options, this becomes a feasibility question: does there exist a lottery over options that clears all stakeholders’ acceptability bars? We study a query model where the algorithm proposes lotteries and receives only binary accept/reject feedback. We give deterministic and randomized algorithms that either find a unanimously acceptable lottery or certify infeasibility; adaptivity […]

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Here is a list of ~1,200 ICLR 2026 accepted papers that have associated public code, data, or a demo link available. The links are directly extracted from their paper submissions. This is approximately 22% of the 5,300+ accepted papers. The List: https://www.paperdigest.org/2026/04/iclr-2026-papers-with-code-data/ The ‘code’ link in the last column takes you directly to the code base (GitHub, official site, etc.). Some code repositories may not be made fully public until the conference officially begins. ICLR 2026 will be […]

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Machine learning has become a powerful tool for discovering governing laws of dynamical systems from data. However, most existing approaches degrade severely when observations are sparse, noisy, or irregularly sampled. In this work, we address the problem of learning symbolic representations of nonlinear Hamiltonian dynamical systems under extreme data scarcity by explicitly incorporating physical structure into the learning architecture. We introduce Adaptable Symplectic Recurrent Neural Networks (ASRNNs), a parameter-cognizant, structure-preserving model that combines Hamiltonian learning with symplectic recurrent […]

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I’ve been looking at a recurring failure pattern across AI systems in production. Not model failure, or data quality or infrastructure. Something else. Where system continues to operate exactly as designed, models run, outputs look valid, pipelines execute and governance signs off But the underlying assumptions have shifted. So you end up with decisions that are technically correct, but contextually wrong. Most organisations respond by tightening controls, reducing overrides or increasing monitoring. Which just reinforces the same behaviour. […]

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I am thinking about becoming a research engineer, and want to ask your advice on how realistic it is, and which strategies make sense in my situation. About myself: I am in the US, have extensive experience as a Software Engineer (including Staff+ position at one of the top companies), have a math heavy CS degree, and have taken additional ML courses from one of schools offering them to outsiders. I also had applied ML work some time […]

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A major AI executive heading to the White House is not a novelty but a sign of where power is moving. When Dario Amodei showed up for the high-level talks, the question wasn’t just about the technology, it was about who’s actually in control. AI is gradually becoming a tool for geopolitics, and companies like Anthropic find themselves negotiating directly with governments about how far their technology should reach. Right at the center of these talks is a […]

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Key Highlights: The internet has always struggled to figure out who’s real and who’s not, but now that AI-generated profiles are everywhere, the issue’s gotten worse. There are convincing synthetic identities that act just like real people everywhere. Sam Altman’s World project sees itself as the fix, aiming to build a universal system to separate humans from machines. The newest step is to plug World ID into Tinder, one of the biggest dating platforms out there. Tinder’s betting […]

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Human mobility prediction is a critical task but remains challenging due to its complexity and variability across populations and regions. Recently, large language models (LLMs) have made progress in zero-shot prediction, but existing methods suffer from limited interpretability (due to black-box reasoning), lack of iterative learning from new data, and poor transferability. In this paper, we introduce textbf{ARMove}, a fully transferable framework for predicting human mobility through agentic reasoning. To address these limitations, ARMove employs standardized feature management […]

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