Flow-Factory: A Unified Framework for Reinforcement Learning in Flow-Matching Models
arXiv:2602.12529v1 Announce Type: new Abstract: Reinforcement learning has emerged as a promising paradigm for aligning diffusion and flow-matching models with human preferences, yet practitioners face fragmented codebases, model-specific implementations, and engineering complexity. We introduce Flow-Factory, a unified framework that decouples...
VI-CuRL: Stabilizing Verifier-Independent RL Reasoning via Confidence-Guided Variance Reduction
arXiv:2602.12579v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a dominant paradigm for enhancing Large Language Models (LLMs) reasoning, yet its reliance on external verifiers limits its scalability. Recent findings suggest that RLVR primarily functions...
Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction
arXiv:2602.12613v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) are pivotal in processing dynamic graphs. However, existing TGNNs primarily target one-time predictions for a given temporal span, whereas many practical applications require continuous predictions, that predictions are issued frequently...
Flow Matching from Viewpoint of Proximal Operators
arXiv:2602.12683v1 Announce Type: new Abstract: We reformulate Optimal Transport Conditional Flow Matching (OT-CFM), a class of dynamical generative models, showing that it admits an exact proximal formulation via an extended Brenier potential, without assuming that the target distribution has a...
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts - ACL Anthology
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing - ACL Anthology
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts - ACL Anthology
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track - ACL Anthology
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts - ACL Anthology
Stanford University
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Artificial Intelligence and Law
This journal seeks papers that address the development of formal or computational models of legal knowledge, reasoning, and decision making. It also includes ...
ODW creates business value through website design and development — Osborn Design Works
Osborn Design Works (ODW) designs and develops high-performance websites and apps, leveraging product design, UI/UX design, and marketing design to create business value.
Philosophy Fellowship 2023 | CAIS Project
The Center for AI Safety is offering grants for philosophers to pursue research in conceptual AI safety.
AI Safety, Ethics and Society Course
The AI Safety, Ethics, and Society Course would be held virtually and be completely free. It would be part-time and we expect that it will require a time commitment of 3-5 hours per week for 10 weeks.
Artificial Power: 2025 Landscape Report - AI Now Institute
In the aftermath of the “AI boom,” this report examines how the push to integrate AI products everywhere grants AI companies - and the tech oligarchs that run them - power that goes far beyond their deep pockets.
North Star Data Center Policy Toolkit: State and Local Policy Interventions to Stop Rampant AI Data Center Expansion - AI Now Institute
A Buddhist Perspective on AI: Cultivating freedom of attention and true diversity in an AI future
The AI-facilitated intelligence revolution is claimed by some to be setting humanity on a glidepath into utopian futures of nearly effortless satisfaction and frictionless choice. We should beware.
Paris AI Safety Breakfast #4: Rumman Chowdhury
The fourth of our 'AI Safety Breakfasts' event series, featuring Dr. Rumman Chowdhury on algorithmic auditing, "right to repair" AI systems, and the AI Safety and Action Summits.
The Global Minimum Tax and the Future of International Taxation
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Trump FTC wants Apple News to promote more Fox News and Breitbart stories
FTC claims Apple News suppresses conservatives, cites study by pro-Trump group.
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