Tootfinder

My phone being at 23% charge vs. finishing listening to the rest of this new very long, death doomy Perishing album. Which shall prevail
https://perishing.bandcamp.com/album/malicious-acropolis-unveiled

Extended AI Interactions Shape Sycophancy and Perspective Mimesis
Shomik Jain, Charlotte Park, Matheus Mesquita Viana, Ashia Wilson, Dana Calacci
https://arxiv.org/abs/2509.12517

Extended AI Interactions Shape Sycophancy and Perspective Mimesis
We investigate whether long-context interactions between users and LLMs lead to AI mirroring behaviors. We focus on two forms of mirroring: (1) sycophancy -- the tendency of models to be overly agreeable with users, and (2) perspective mimesis -- the extent to which models reflect a user's perspective. Using two weeks of interaction context collected from 38 users, we compare model responses with and without long-context for two tasks: political explanations and personal advice. Our results dem…

Dynamic Decision Modeling for Viable Short and Long Term Production Policies: An HJB Approach
Achraf Bouhmady, Mustapha Serhani, Nadia Raissi
https://arxiv.org/abs/2509.12205 ht…

Dynamic Decision Modeling for Viable Short and Long Term Production Policies: An HJB Approach
This study introduces a mathematical framework to investigate the viability and reachability of production systems under constraints. We develop a model that incorporates key decision variables, such as pricing policy, quality investment, and advertising, to analyze short-term tactical decisions and long-term strategic outcomes. In the short term, we constructed a capture basin that defined the initial conditions under which production viability constraints were satisfied within the target zone…

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
Humza Ashraf, Syed Muhammad Danish, Aris Leivadeas, Yazan Otoum, Zeeshan Sattar
https://arxiv.org/abs/2508.08332

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
Large Language Models (LLMs) are widely used for code generation. However, commercial models like ChatGPT require significant computing power, which leads to high energy use and carbon emissions. This has raised concerns about their environmental impact. In this study, we evaluate open-source Small Language Models (SLMs) trained explicitly for code generation and compare their performance and energy efficiency against large LLMs and efficient human-written Python code. The goal is to investigat…

Humanoid Robot Acrobatics Utilizing Complete Articulated Rigid Body Dynamics
Gerald Brantner
https://arxiv.org/abs/2508.08258 https://arxiv.org/pdf/2508.08…

Humanoid Robot Acrobatics Utilizing Complete Articulated Rigid Body Dynamics
Endowing humanoid robots with the ability to perform highly dynamic motions akin to human-level acrobatics has been a long-standing challenge. Successfully performing these maneuvers requires close consideration of the underlying physics in both trajectory optimization for planning and control during execution. This is particularly challenging due to humanoids' high degree-of-freedom count and associated exponentially scaling complexities, which makes planning on the explicit equations of motio…

Update on the Estlink-2 #subseacable cut last December:
"Finnish authorities [...] have charged the captain and two senior officers of a Russia-linked vessel that damaged undersea cables last year between Finland and Estonia."

Finland charges top officers of Russia-linked vessel that damaged undersea cables
Finnish authorities say they have charged the captain and two senior officers of a Russia-linked vessel that damaged undersea cables last year between Finland and Estonia. Monday's statement says they denied the allegations of aggravated criminal mischief and aggravated interference with communications. Authorities have said the vessel dragged its anchor to damage the Estlink-2 power cable and communication links between Finland and Estonia on Dec. 25. The Kremlin previously denied involvement …

The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
Pengrui Han, Rafal Kocielnik, Peiyang Song, Ramit Debnath, Dean Mobbs, Anima Anandkumar, R. Michael Alvarez
https://arxiv.org/abs/2509.03730

The Personality Illusion: Revealing Dissociation Between Self-Reports & Behavior in LLMs
Personality traits have long been studied as predictors of human behavior.Recent advances in Large Language Models (LLMs) suggest similar patterns may emerge in artificial systems, with advanced LLMs displaying consistent behavioral tendencies resembling human traits like agreeableness and self-regulation. Understanding these patterns is crucial, yet prior work primarily relied on simplified self-reports and heuristic prompting, with little behavioral validation. In this study, we systematicall…

Der nächste Termin unserer Reihe „Juniorteams laden ein“ steht an!
Dieses Mal ist Lisa Steffney von equaletics e.V. einladen. Der Verein setzt sich für Chancengerechtigkeit im Sport ein. Lisa berichtet darüber, wie Chancengleichheit im Ehrenamt möglich ist.
Anmeldung über den Link: https://forms.office.com/e/56ESm90ZH5

Inductive Bias Extraction and Matching for LLM Prompts
Christian M. Angel, Francis Ferraro
https://arxiv.org/abs/2508.10295 https://arxiv.org/pdf/2508.1029…

Inductive Bias Extraction and Matching for LLM Prompts
The active research topic of prompt engineering makes it evident that LLMs are sensitive to small changes in prompt wording. A portion of this can be ascribed to the inductive bias that is present in the LLM. By using an LLM's output as a portion of its prompt, we can more easily create satisfactory wording for prompts. This has the effect of creating a prompt that matches the inductive bias in model. Empirically, we show that using this Inductive Bias Extraction and Matching strategy improves …

Toward Green Code: Prompting Small Language Models for Energy-Efficient Code Generation
Humza Ashraf, Syed Muhammad Danish, Zeeshan Sattar
https://arxiv.org/abs/2509.09947 https…

Toward Green Code: Prompting Small Language Models for Energy-Efficient Code Generation
There is a growing concern about the environmental impact of large language models (LLMs) in software development, particularly due to their high energy use and carbon footprint. Small Language Models (SLMs) offer a more sustainable alternative, requiring fewer computational resources while remaining effective for fundamental programming tasks. In this study, we investigate whether prompt engineering can improve the energy efficiency of SLMs in code generation. We evaluate four open-source SLMs…