Tootfinder

Secret-Protected Evolution for Differentially Private Synthetic Text Generation
Tianze Wang, Zhaoyu Chen, Jian Du, Yingtai Xiao, Linjun Zhang, Qiang Yan
https://arxiv.org/abs/2510.10990

Secret-Protected Evolution for Differentially Private Synthetic Text Generation
Text data has become extremely valuable on large language models (LLMs) and even lead to general artificial intelligence (AGI). A lot of high-quality text in the real world is private and cannot be freely used due to privacy concerns. Therefore, differentially private (DP) synthetic text generation has been proposed, aiming to produce high-utility synthetic data while protecting sensitive information. However, existing DP synthetic text generation imposes uniform guarantees that often overprote…

UXer-AI Collaboration Process for Enhancing Trust
Harin Yoon, Dongwhan Kim, Changhoon Oh, Soojin Jun
https://arxiv.org/abs/2510.11087 https://arxiv.org/pdf…

UXer-AI Collaboration Process for Enhancing Trust
In recent years, discussions on integrating Artificial Intelligence (AI) into UX design have intensified. However, the practical application of AI tools in design is limited by their operation within overly simplified scenarios, inherent complexity and unpredictability, and a general lack of relevant education. This study proposes an effective UXer-AI collaboration process to address these issues and seeks to identify efficient AI collaboration strategies through a series of user studies. In a …

Microsoft AI CEO Mustafa Suleyman says his new superintelligence team will build "frontier-grade research capability" and Microsoft needs AI self-sufficiency (Ashley Stewart/Business Insider)
https://www.businessinsider.com/microsoft-

OpenAI used to prevent Microsoft pursuing AGI. Now, the software giant is free to compete, Mustafa Suleyman says.
A renegotiated deal lets Microsoft independently pursue artificial general intelligence. Suleyman is seizing the moment.

Syntax is not Semantics
Language is not the same as intelligence.
The entire AI bubble is built on ignoring that.
https://www.theverge.com/ai-artificial-intelligence/827820/large-language-models-ai-intellige…

Large language mistake
Neuroscience indicates language is distinct from thought, raising questions about whether AI large language models are a viable path to artificial general intelligence.

From Mimicry to True Intelligence (TI) - A New Paradigm for Artificial General Intelligence
Meltem Subasioglu, Nevzat Subasioglu
https://arxiv.org/abs/2509.14474 https://…

From Mimicry to True Intelligence (TI) - A New Paradigm for Artificial General Intelligence
The debate around Artificial General Intelligence (AGI) remains open due to two fundamentally different goals: replicating human-like performance versus replicating human-like cognitive processes. We argue that current performance-based definitions are inadequate because they provide no clear, mechanism-focused roadmap for research, and they fail to properly define the qualitative nature of genuine intelligence. Drawing inspiration from the human brain, we propose a new paradigm that shifts the…

"Ohio Bill Would Require Watermarks on AI Imagery"
How exactly does a state enforce this? 🤔 "...it could place restrictions on a consumer's legal uses of a product, or it could place restrictions on what type of functions a producer's product can actually produce."
http…

At the UN, the US rejected calls for collaborative efforts around AI governance, even as many leaders endorsed a need for urgent international collaboration (Jared Perlo/NBC News)
https://www.nbcnews.com/tech/tech-news/us-rejects-in…

U.S. rejects international AI oversight at U.N. General Assembly
The United States clashed with world leaders over artificial intelligence at the United Nations General Assembly this week.

Guten Morgen. Es ist überraschenderweise wieder Dienstag und damit #DNIPBriefing-Tag!
1️⃣ Wir nehmen die Behauptungen von Musk, Zuckerberg oder Altman unter die Lupe, dass die künstliche Superintelligenz oder Artificial General Intelligence (AGI) möglicherweise schon 2026 so weit sei.
Ein hervorragender Artikel von The Verge zeigt das wundervoll auf.
Alle Chatbots basieren…

Assisting the Grading of a Handwritten General Chemistry Exam with Artificial Intelligence
Jan Cvengros, Gerd Kortemeyer
https://arxiv.org/abs/2509.10591 https://

Assisting the Grading of a Handwritten General Chemistry Exam with Artificial Intelligence
We explore the effectiveness and reliability of an artificial intelligence (AI)-based grading system for a handwritten general chemistry exam, comparing AI-assigned scores to human grading across various types of questions. Exam pages and grading rubrics were uploaded as images to account for chemical reaction equations, short and long open-ended answers, numerical and symbolic answer derivations, drawing, and sketching in pencil-and-paper format. Using linear regression analyses and psychometr…

RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation
Chao Yu, Yuanqing Wang, Zhen Guo, Hao Lin, Si Xu, Hongzhi Zang, Quanlu Zhang, Yongji Wu, Chunyang Zhu, Junhao Hu, Zixiao Huang, Mingjie Wei, Yuqing Xie, Ke Yang, Bo Dai, Zhexuan Xu, Xiangyuan Wang, Xu Fu, Zhihao Liu, Kang Chen, Weilin Liu, Gang Liu, Boxun Li, Jianlei Yang, Zhi Yang, Guohao Dai, Yu Wang

RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation
Reinforcement learning (RL) has demonstrated immense potential in advancing artificial general intelligence, agentic intelligence, and embodied intelligence. However, the inherent heterogeneity and dynamicity of RL workflows often lead to low hardware utilization and slow training on existing systems. In this paper, we present RLinf, a high-performance RL training system based on our key observation that the major roadblock to efficient RL training lies in system flexibility. To maximize flexib…

A profile of OpenAI President Greg Brockman and his role in the company's $1.4T infrastructure buildout that's required to reach AGI (Sharon Goldman/Fortune)
https://fortune.com/2025/11/05/openai-greg-brockman-ai-infrastructure-data-c…

Meet OpenAI’s master builder: Greg Brockman is steering a $1.4 trillion infrastructure surge with stakes that go far beyond AI
As OpenAI’s president, Brockman is focused on “completing the mission” of moving beyond AI to artificial general intelligence (AGI).

Why must I select AND click submit on the 4 remaining Connection tiles after I have 3 good categories? There’s nothing else to be done. I play on a computer. In a world where we’re told that we are 6 to 24 months away from Artificial General Intelligence, it seems like the game could select and submit them for me 🤷
#Connections

Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning
Sigmund Hennum H{\o}eg, Aksel Vaaler, Chaoqi Liu, Olav Egeland, Yilun Du
https://arxiv.org/abs/2509.21983 http…

Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning
Constructing robots to accomplish long-horizon tasks is a long-standing challenge within artificial intelligence. Approaches using generative methods, particularly Diffusion Models, have gained attention due to their ability to model continuous robotic trajectories for planning and control. However, we show that these models struggle with long-horizon tasks that involve complex decision-making and, in general, are prone to confusing different modes of behavior, leading to failure. To remedy thi…

Embodied AI: From LLMs to World Models
Tongtong Feng, Xin Wang, Yu-Gang Jiang, Wenwu Zhu
https://arxiv.org/abs/2509.20021 https://arxiv.org/pdf/2509.20021

Embodied AI: From LLMs to World Models
Embodied Artificial Intelligence (AI) is an intelligent system paradigm for achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications and driving the evolution from cyberspace to physical systems. Recent breakthroughs in Large Language Models (LLMs) and World Models (WMs) have drawn significant attention for embodied AI. On the one hand, LLMs empower embodied AI via semantic reasoning and task decomposition, bringing high-level natural language instruc…

A Decision Theoretic Perspective on Artificial Superintelligence: Coping with Missing Data Problems in Prediction and Treatment Choice
Jeff Dominitz, Charles F. Manski
https://arxiv.org/abs/2509.12388 …

A Decision Theoretic Perspective on Artificial Superintelligence: Coping with Missing Data Problems in Prediction and Treatment Choice
Enormous attention and resources are being devoted to the quest for artificial general intelligence and, even more ambitiously, artificial superintelligence. We wonder about the implications for our methodological research, which aims to help decision makers cope with what econometricians call identification problems, inferential problems in empirical research that do not diminish as sample size grows. Of particular concern are missing data problems in prediction and treatment choice. Essential…

The three main doctrines on the future of AI
Alex Amadori, Eva Behrens, Gabriel Alfour, Andrea Miotti
https://arxiv.org/abs/2509.20050 https://arxiv.org/pd…

The three main doctrines on the future of AI
This paper develops a taxonomy of expert perspectives on the risks and likely consequences of artificial intelligence, with particular focus on Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI). Drawing from primary sources, we identify three predominant doctrines: (1) The dominance doctrine, which predicts that the first actor to create sufficiently advanced AI will attain overwhelming strategic superiority sufficient to cheaply neutralize its opponents' defenses; (2…

Memo: California's AG says OpenAI's restructuring has "no impact" on other cases, likely referring to Elon Musk's lawsuit against OpenAI over its restructuring (Rocket Drew/The Information)
https://www.theinformation.com/briefings/m…

Musk Suit Unlikely to Unwind OpenAI Restructure
A memo from California’s attorney general suggested that Elon Musk’s federal lawsuit against OpenAI will be unaffected by the artificial intelligence startup’s restructuring. But now that the restructuring has occurred, it may be hard to unwind the change even if Musk wins. Both the attorneys general for Delaware, where OpenAI is incorporated, and California, where it is headquartered, had

AssoCiAm: A Benchmark for Evaluating Association Thinking while Circumventing Ambiguity
Yifan Liu, Wenkuan Zhao, Shanshan Zhong, Jinghui Qin, Mingfu Liang, Zhongzhan Huang, Wushao Wen
https://arxiv.org/abs/2509.14171

AssoCiAm: A Benchmark for Evaluating Association Thinking while Circumventing Ambiguity
Recent advancements in multimodal large language models (MLLMs) have garnered significant attention, offering a promising pathway toward artificial general intelligence (AGI). Among the essential capabilities required for AGI, creativity has emerged as a critical trait for MLLMs, with association serving as its foundation. Association reflects a model' s ability to think creatively, making it vital to evaluate and understand. While several frameworks have been proposed to assess associative abi…

Learning in Stackelberg Markov Games
Jun He, Andrew L. Liu, Yihsu Chen
https://arxiv.org/abs/2509.16296 https://arxiv.org/pdf/2509.16296

Learning in Stackelberg Markov Games
Designing socially optimal policies in multi-agent environments is a fundamental challenge in both economics and artificial intelligence. This paper studies a general framework for learning Stackelberg equilibria in dynamic and uncertain environments, where a single leader interacts with a population of adaptive followers. Motivated by pressing real-world challenges such as equitable electricity tariff design for consumers with distributed energy resources (such as rooftop solar and energy stor…

Embodied AI: From LLMs to World Models
Tongtong Feng, Xin Wang, Yu-Gang Jiang, Wenwu Zhu
https://arxiv.org/abs/2509.20021 https://arxiv.org/pdf/2509.20021

Embodied AI: From LLMs to World Models
Embodied Artificial Intelligence (AI) is an intelligent system paradigm for achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications and driving the evolution from cyberspace to physical systems. Recent breakthroughs in Large Language Models (LLMs) and World Models (WMs) have drawn significant attention for embodied AI. On the one hand, LLMs empower embodied AI via semantic reasoning and task decomposition, bringing high-level natural language instruc…

Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence
Myra Cheng, Cinoo Lee, Pranav Khadpe, Sunny Yu, Dyllan Han, Dan Jurafsky
https://arxiv.org/abs/2510.01395 h…

Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence
Both the general public and academic communities have raised concerns about sycophancy, the phenomenon of artificial intelligence (AI) excessively agreeing with or flattering users. Yet, beyond isolated media reports of severe consequences, like reinforcing delusions, little is known about the extent of sycophancy or how it affects people who use AI. Here we show the pervasiveness and harmful impacts of sycophancy when people seek advice from AI. First, across 11 state-of-the-art AI models, we …

Benchmarking Agentic Systems in Automated Scientific Information Extraction with ChemX
Anastasia Vepreva, Julia Razlivina, Maria Eremeeva, Nina Gubina, Anastasia Orlova, Aleksei Dmitrenko, Ksenya Kapranova, Susan Jyakhwo, Nikita Vasilev, Arsen Sarkisyan, Ivan Yu. Chernyshov, Vladimir Vinogradov, Andrei Dmitrenko
https://arxiv.org/abs/2510.…

Benchmarking Agentic Systems in Automated Scientific Information Extraction with ChemX
The emergence of agent-based systems represents a significant advancement in artificial intelligence, with growing applications in automated data extraction. However, chemical information extraction remains a formidable challenge due to the inherent heterogeneity of chemical data. Current agent-based approaches, both general-purpose and domain-specific, exhibit limited performance in this domain. To address this gap, we present ChemX, a comprehensive collection of 10 manually curated and domain…

Crosslisted article(s) found for econ.GN. https://arxiv.org/list/econ.GN/new
[1/1]:
- Leveraging Artificial Intelligence as a Strategic Growth Catalyst for Small and Medium-sized Ente...
Oluwatosin Agbaakin (Indiana University Indianapolis)

A Scenario-Driven Cognitive Approach to Next-Generation AI Memory
Linyue Cai, Yuyang Cheng, Xiaoding Shao, Huiming Wang, Yong Zhao, Wei Zhang, Kang Li
https://arxiv.org/abs/2509.13235

A Scenario-Driven Cognitive Approach to Next-Generation AI Memory
As artificial intelligence advances toward artificial general intelligence (AGI), the need for robust and human-like memory systems has become increasingly evident. Current memory architectures often suffer from limited adaptability, insufficient multimodal integration, and an inability to support continuous learning. To address these limitations, we propose a scenario-driven methodology that extracts essential functional requirements from representative cognitive scenarios, leading to a unifie…

The Indispensable Role of User Simulation in the Pursuit of AGI
Krisztian Balog, ChengXiang Zhai
https://arxiv.org/abs/2509.19456 https://arxiv.org/pdf/250…

The Indispensable Role of User Simulation in the Pursuit of AGI
Progress toward Artificial General Intelligence (AGI) faces significant bottlenecks, particularly in rigorously evaluating complex interactive systems and acquiring the vast interaction data needed for training adaptive agents. This paper posits that user simulation -- creating computational agents that mimic human interaction with AI systems -- is not merely a useful tool, but is a critical catalyst required to overcome these bottlenecks and accelerate AGI development. We argue that realistic …

The Indispensable Role of User Simulation in the Pursuit of AGI
Krisztian Balog, ChengXiang Zhai
https://arxiv.org/abs/2509.19456 https://arxiv.org/pdf/250…

The Indispensable Role of User Simulation in the Pursuit of AGI
Progress toward Artificial General Intelligence (AGI) faces significant bottlenecks, particularly in rigorously evaluating complex interactive systems and acquiring the vast interaction data needed for training adaptive agents. This paper posits that user simulation -- creating computational agents that mimic human interaction with AI systems -- is not merely a useful tool, but is a critical catalyst required to overcome these bottlenecks and accelerate AGI development. We argue that realistic …

Rationality Check! Benchmarking the Rationality of Large Language Models
Zhilun Zhou, Jing Yi Wang, Nicholas Sukiennik, Chen Gao, Fengli Xu, Yong Li, James Evans
https://arxiv.org/abs/2509.14546

Rationality Check! Benchmarking the Rationality of Large Language Models
Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artificial general intelligence. With human-like capabilities, LLMs have been used to simulate humans and serve as AI assistants across many applications. As a result, great concern has arisen about whether and under what circumstances LLMs think and behave like real human agents. Rationality is among the most important con…

VCBench: Benchmarking LLMs in Venture Capital
Rick Chen, Joseph Ternasky, Afriyie Samuel Kwesi, Ben Griffin, Aaron Ontoyin Yin, Zakari Salifu, Kelvin Amoaba, Xianling Mu, Fuat Alican, Yigit Ihlamur
https://arxiv.org/abs/2509.14448

VCBench: Benchmarking LLMs in Venture Capital
Benchmarks such as SWE-bench and ARC-AGI demonstrate how shared datasets accelerate progress toward artificial general intelligence (AGI). We introduce VCBench, the first benchmark for predicting founder success in venture capital (VC), a domain where signals are sparse, outcomes are uncertain, and even top investors perform modestly. At inception, the market index achieves a precision of 1.9%. Y Combinator outperforms the index by a factor of 1.7x, while tier-1 firms are 2.9x better. VCBench p…