January 2026

For most of the internet era, educational technology followed a familiar pattern: digitize the textbook, put worksheets on a screen, maybe add a video. The goal was efficiency. Faster distribution. Easier grading. More content, more quickly. But that model is starting to feel dated. Today’s learners don’t just want information delivered. They expect to interact with it. Remix it. Build on top of it. The question is no longer whether technology belongs in education; it’s whether our education […]

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To promote cooperation in Multi-Agent Reinforcement Learning, the reward signals of all agents can be aggregated together, forming global rewards that are commonly known as the fully cooperative setting. However, global rewards are usually noisy because they contain the contributions of all agents, which have to be resolved in the credit assignment process. On the other hand, using local reward benefits from faster learning due to the separation of agents’ contributions, but can be suboptimal as agents myopically […]

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Many-Task Learning refers to the setting where a large number of related tasks need to be learned, the exact relationships between tasks are not known. We introduce the Cascaded Transfer Learning, a novel many-task transfer learning paradigm where information (e.g. model parameters) cascades hierarchically through tasks that are learned by individual models of the same class, while respecting given budget constraints. The cascade is organized as a rooted tree that specifies the order in which tasks are learned […]

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Victoria, Seychelles, January 29, 2026 MEXC, the fastest-growing global cryptocurrency exchange, redefining a user-first approach to digital assets through true zero-fee trading, today reported significant growth in precious metals futures trading, with gold futures market share reaching 47% on January 25, 2026, and single-day trading volume hitting $555 million. MEXC’s GOLD Futures market share grew from 2.4% in early December 2025 to 47% by January 25, 2026—a 20-fold increase over two months. The platform surpassed competitors to capture […]

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Victoria, Seychelles, January 29, 2026 MEXC, the fastest-growing global cryptocurrency exchange, redefining a user-first approach to digital assets through true Zero-Fee trading, today released its 2025 Zero-Fee Strategy Annual Report. The ongoing commitment not only saved users a total of 1.1 billion USDT in fees but also bolsters both mainstream growth and emerging asset visibility, driving balanced development across the entire crypto landscape. The platform’s removal of fees across 3,026 spot trading pairs and 203 futures pairs resulted […]

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Byline: Keith Belanger AI projects have a way of surfacing data problems that data teams used to be able to work around. That’s because analytical data allowed for a wide margin of error, and AI simply doesn’t. AI models don’t tolerate ambiguity, and decisions made at machine speed magnify every flaw hiding upstream. What once failed quietly now fails loudly, and often publicly. AI failures are often dismissed as experimental growing pains. In reality, they’re revealing the weakness […]

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We study partial-feedback online learning, where each instance admits a set of correct labels, but the learner only observes one correct label per round; any prediction within the correct set is counted as correct. This model captures settings such as language generation, where multiple responses may be valid but data provide only a single reference. We give a near-complete characterization of minimax regret for both deterministic and randomized learners in the set-realizable regime, i.e., in the regime where […]

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LLM role-playing, i.e., using LLMs to simulate specific personas, has emerged as a key capability in various applications, such as companionship, content creation, and digital games. While current models effectively capture character tones and knowledge, simulating the inner thoughts behind their behaviors remains a challenge. Towards cognitive simulation in LLM role-play, previous efforts mainly suffer from two deficiencies: data with high-quality reasoning traces, and reliable reward signals aligned with human preferences. In this paper, we propose HER, a […]

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