An Update on Heroku An ominous headline to see on the official Heroku blog and yes, it’s bad news. Today, Heroku is transitioning to a sustaining engineering model focused on stability, security, reliability, and support. Heroku remains an actively supported, production-ready platform, with an emphasis on maintaining quality and operational excellence rather than introducing new features. We know changes like this can raise questions, and we want to be clear about what this means for customers. Based on […]

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arXiv:2603.16889v1 Announce Type: new Abstract: Reliable and interpretable automated assessment of second-language (L2) speech remains a central challenge, as large speech-language models (SpeechLLMs) often struggle to align with the nuanced variability of human raters. To address this, we introduce a rubric-guided reasoning framework that explicitly encodes multi-aspect human assessment criteria: accuracy, fluency, and prosody, while calibrating model uncertainty to capture natural rating variability. We fine-tune the Qwen2-Audio-7B-Instruct model using multi-rater human judgments and develop an uncertainty-calibrated regression approach […]

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arXiv:2602.17694v1 Announce Type: new Abstract: With the rapid development of large language models (LLMs), an increasing number of applications leverage cloud-based LLM APIs to reduce usage costs. However, since cloud-based models’ parameters and gradients are agnostic, users have to manually or use heuristic algorithms to adjust prompts for intervening LLM outputs, which requiring costly optimization procedures. In-context learning (ICL) has recently emerged as a promising paradigm that enables LLMs to adapt to new tasks using examples provided within […]

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Table of Links Abstract and 1. Introduction Some recent trends in theoretical ML 2.1 Deep Learning via continuous-time controlled dynamical system 2.2 Probabilistic modeling and inference in DL 2.3 Deep Learning in non-Euclidean spaces 2.4 Physics Informed ML Kuramoto model 3.1 Kuramoto models from the geometric point of view 3.2 Hyperbolic geometry of Kuramoto ensembles 3.3 Kuramoto models with several globally coupled sub-ensembles Kuramoto models on higher-dimensional manifolds 4.1 Non-Abelian Kuramoto models on Lie groups 4.2 Kuramoto models […]

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OpenAI is deeply embedded in political and social discourse because AI itself is. A traditional way to shape public opinion, PR, is not effective enough to help OpenAI deal with the kinds of challenges the company faces. So OpenAI bought a media company. On April 2, OpenAI announced it is acquiring TBPN, the daily tech talk show founded in 2024 by John Coogan and Jordi Hays. OpenAI says the deal is meant to accelerate global conversations around AI, […]

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arXiv:2603.03307v1 Announce Type: new Abstract: Epistemic Network Analysis (ENA) is a method for investigating the relational structure of concepts in text by representing co-occurring concepts as networks. Traditional ENA, however, relies heavily on manual expert coding, which limits its scalability and real-world applicability to large text corpora. Topic modeling provides an automated approach to extracting concept-level representations from text and can serve as an alternative to manual coding. To tackle this limitation, the present study merges BERTopic with […]

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I recently joined Alignerr for a different technical role and noticed they’re looking for people with hands-on MuJoCo / robotics simulation / reinforcement learning experience. The role seems best suited for people who have worked with MuJoCo, MJCF/XML, Gymnasium/dm_control, reward shaping, PPO/SAC/TD3, physics debugging, and robot control. It’s remote contractor work. I don’t want to oversell it because project availability can vary, but the listed rate is high and it may be worth checking out if you already […]

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arXiv:2601.07144v2 Announce Type: replace Abstract: Ensuring fairness in matching algorithms is a key challenge in allocating scarce resources and positions. Focusing on Optimal Transport (OT), we introduce a novel notion of group fairness requiring that the probability of matching two individuals from any two given groups in the OT plan satisfies a predefined target. We first propose a modified Sinkhorn algorithm to compute perfectly fair transport plans efficiently. Since exact fairness can significantly degrade matching quality in practice, […]

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arXiv:2601.07966v1 Announce Type: new Abstract: The acceleration of materials discovery requires digital platforms that go beyond data repositories to embed learning, optimization, and decision-making directly into research workflows. We introduce DataScribe, an AI-native, cloud-based materials discovery platform that unifies heterogeneous experimental and computational data through ontology-backed ingestion and machine-actionable knowledge graphs. The platform integrates FAIR-compliant metadata capture, schema and unit harmonization, uncertainty-aware surrogate modeling, and native multi-objective multi-fidelity Bayesian optimization, enabling closed-loop propose-measure-learn workflows across experimental and computational […]

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I deployed a staking vault on Sepolia and got it verified on Etherscan with a green checkmark. The source code contains a storage write that does not exist in the compiled bytecode, due to a known Solidity optimizer bug (SOL-2022-7). The verification confirms the build is reproducible. It does not confirm the bytecode does what the source says.

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