March 2026

Interactive recommender systems (IRS) are increasingly optimized with Reinforcement Learning (RL) to capture the sequential nature of user-system dynamics. However, existing fairness-aware methods often suffer from a fundamental oversight: they assume the observed user state is a faithful representation of true preferences. In reality, implicit feedback is contaminated by popularity-driven noise and exposure bias, creating a distorted state that misleads the RL agent. We argue that the persistent conflict between accuracy and fairness is not merely a reward-shaping […]

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Continual learning is a long-standing challenge in robot policy learning, where a policy must acquire new skills over time without catastrophically forgetting previously learned ones. While prior work has extensively studied continual learning in relatively small behavior cloning (BC) policy models trained from scratch, its behavior in modern large-scale pretrained Vision-Language-Action (VLA) models remains underexplored. In this work, we found that pretrained VLAs are remarkably resistant to forgetting compared with smaller policy models trained from scratch. Simple Experience […]

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New York, United States, March 3rd, 2026/Chainwire/–Threshold Network, the decentralized blockchain protocol behind tBTC, has introduced an update to its decentralized application featuring an all-in-one Unified Bitcoin App that enables users to route Bitcoin across major chains through a single interface. This new unified routing interface brings minting, redeeming, bridging, tracking, and native BTC swaps into a single application: The Threshold App. Users can now move Bitcoin across ecosystems through a coordinated system, rather than stitching together multiple […]

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Relational Databases (RDBs) are the backbone of modern business, yet they lack foundation models comparable to those in text or vision. A key obstacle is that high-quality RDBs are private, scarce and structurally heterogeneous, making internet-scale pre-training infeasible. To overcome this data scarcity, We introduce $textbf{RDB-PFN}$, the first relational foundation model trained purely via $textbf{synthetic data}$. Inspired by Prior-Data Fitted Networks (PFNs) where synthetic data generated from Structural Causal Models (SCMs) enables reasoning on single tables, we design […]

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Toronto, Canada, March 3rd, 2026/–Paradex has announced that the Token Generation Event for its native token, $DIME, is expected to take place soon. The launch represents the next phase in the exchange’s development. Institutional Background and Market Growth Paradex was developed by the team behind Paradigm, an institutional crypto derivatives liquidity network that has processed more than $1 trillion in trading volume. That background is reflected in Paradex’s focus on execution quality, capital efficiency, and market structure. Since […]

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I’ve been building a system to create physics-based humanoid characters in Unity that can learn through reinforcement learning — and you can physically interact with them in mixed reality on Quest. Today I’m open-sourcing the three packages that make it up. What it does: synth-core — Take any Daz Genesis 8 or Mixamo character, run it through an editor wizard (or one-click right-click menu), and get a fully physics-simulated humanoid with MuJoCo rigid-body dynamics, mesh-based collision geometry, configurable […]

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How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## 6 Ways to Use a Crypto Exchange Aggregator and Save on Swaps By @swapzone [ 7 Min read ] Maximize your crypto swaps! Learn 6 ways an exchange aggregator saves you money. Find the best rates on Bitcoin, Ethereum, & other cryptocurrencies on DEXs. […]

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Accurate predictions of ship trajectories in crowded environments are essential to ensure safety in inland waterways traffic. Recent advances in deep learning promise increased accuracy even for complex scenarios. While the challenge of ship-to-ship awareness is being addressed with growing success, the explainability of these models is often overlooked, potentially obscuring an inaccurate logic and undermining the confidence in their reliability. This study examines an LSTM-based vessel trajectory prediction model by incorporating trained ship domain parameters that provide […]

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We study the Inverse Contextual Bandit (ICB) problem, in which a learner seeks to optimize a policy while an observer, who cannot access the learner’s rewards and only observes actions, aims to recover the underlying problem parameters. During the learning process, the learner’s behavior naturally transitions from exploration to exploitation, resulting in non-stationary action data that poses significant challenges for the observer. To address this issue, we propose a simple and effective framework called Two-Phase Suffix Imitation. The […]

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