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Source: Meta has hired highly influential OpenAI researcher Trapit Bansal to work on its AI reasoning models under the company's new AI superintelligence unit (Maxwell Zeff/TechCrunch)
https://techcrunch.com/2025/06/26/meta-hi…

Meta hires key OpenAI researcher to work on AI reasoning models | TechCrunch
Meta has hired a key OpenAI researcher to work on AI reasoning models under its new AI superintelligence unit.

Ratjetoe aan rare voer­tuigen op het fietspad maakt Amsterdam ‘moedeloos’: ‘Onze stad is geen pretpark’ | de #Volkskrant
https://www.

via https://www.theguardian.com/technology/2025/may/26/large-language-models-that-power-ai-should-be-publicly-owned:
Matteo Valleriani: "It is time to build public, open-access LLMs for the humanities…

Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
Kai-Robin Lange, Tobias Schmidt, Matthias Reccius, Henrik M\"uller, Michael Roos, Carsten Jentsch
https://arxiv.org/abs/2506.20269

Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
With rapidly evolving media narratives, it has become increasingly critical to not just extract narratives from a given corpus but rather investigate, how they develop over time. While popular narrative extraction methods such as Large Language Models do well in capturing typical narrative elements or even the complex structure of a narrative, applying them to an entire corpus comes with obstacles, such as a high financial or computational cost. We propose a combination of the language understa…

Interview: "Bisherige Prüfungsformate werden durch den Einsatz von KI nutzlos"
Schummeln Schüler mittels KI bei Leistungserhebungen? Einen Hase-und-Igel-Wettlauf sollte man sich in dem Fall sparen und umdenken, erklärt Bernhard Gmeiner.

Hybrid Models for Financial Forecasting: Combining Econometric, Machine Learning, and Deep Learning Models
Dominik Stempie\'n, Robert \'Slepaczuk
https://arxiv.org/abs/2505.19617

Hybrid Models for Financial Forecasting: Combining Econometric, Machine Learning, and Deep Learning Models
This research systematically develops and evaluates various hybrid modeling approaches by combining traditional econometric models (ARIMA and ARFIMA models) with machine learning and deep learning techniques (SVM, XGBoost, and LSTM models) to forecast financial time series. The empirical analysis is based on two distinct financial assets: the S&P 500 index and Bitcoin. By incorporating over two decades of daily data for the S&P 500 and almost ten years of Bitcoin data, the study provides a comp…

Video Perception Models for 3D Scene Synthesis
Rui Huang, Guangyao Zhai, Zuria Bauer, Marc Pollefeys, Federico Tombari, Leonidas Guibas, Gao Huang, Francis Engelmann
https://arxiv.org/abs/2506.20601

Video Perception Models for 3D Scene Synthesis
Traditionally, 3D scene synthesis requires expert knowledge and significant manual effort. Automating this process could greatly benefit fields such as architectural design, robotics simulation, virtual reality, and gaming. Recent approaches to 3D scene synthesis often rely on the commonsense reasoning of large language models (LLMs) or strong visual priors of modern image generation models. However, current LLMs demonstrate limited 3D spatial reasoning ability, which restricts their ability to…

DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
Shansan Gong, Ruixiang Zhang, Huangjie Zheng, Jiatao Gu, Navdeep Jaitly, Lingpeng Kong, Yizhe Zhang
https://arxiv.org/abs/2506.20639

DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation
Diffusion large language models (dLLMs) are compelling alternatives to autoregressive (AR) models because their denoising models operate over the entire sequence. The global planning and iterative refinement features of dLLMs are particularly useful for code generation. However, current training and inference mechanisms for dLLMs in coding are still under-explored. To demystify the decoding behavior of dLLMs and unlock their potential for coding, we systematically investigate their denoising pr…

WhatsApp führt KI-Zusammenfassungen von Chats ein – zuerst in den USA
WhatsApp erweitert die KI-Funktionen: Fortan können Nutzer Zusammenfassungen verpasster Nachrichten mittels Meta AI erstellen lassen – zunächst in den USA.

Enhancing Large Language Models through Structured Reasoning
Yubo Dong, Hehe Fan
https://arxiv.org/abs/2506.20241 https://arxiv.org/p…

Enhancing Large Language Models through Structured Reasoning
Recent Large Language Models (LLMs) have significantly advanced natural language processing and automated decision-making. However, these models still encounter difficulties when performing complex reasoning tasks involving logical deduction and systematic planning, primarily due to their reliance on implicit statistical relationships without structured knowledge representation.Inspired by cognitive science and neurosymbolic AI, we introduce a novel approach to enhance LLMs through explicit str…