Tootfinder

When AI Gets Persuaded, Humans Follow: Inducing the Conformity Effect in Persuasive Dialogue
Rikuo Sasaki, Michimasa Inaba
https://arxiv.org/abs/2510.04229 https://

When AI Gets Persuaded, Humans Follow: Inducing the Conformity Effect in Persuasive Dialogue
Recent advancements in AI have highlighted its application in captology, the field of using computers as persuasive technologies. We hypothesized that the "conformity effect," where individuals align with others' actions, also occurs with AI agents. This study verifies this hypothesis by introducing a "Persuadee Agent" that is persuaded alongside a human participant in a three-party persuasive dialogue with a Persuader Agent. We conducted a text-based dialogue experiment with human participants…

An analysis of nuclear parton distribution function based on Kullback-Leibler divergence
Shu-Man Hu, Ao-Sheng Xiong, Ji Xu, Fu-Sheng Yu, Ji-Xin Yu
https://arxiv.org/abs/2508.05171

An analysis of nuclear parton distribution function based on Kullback-Leibler divergence
In this work, we present an attempt to quantify the difference between nuclear parton distribution functions (nPDFs) in different nuclei and parton distribution functions (PDFs) in free nucleons using the Kullback-Leibler (KL) divergence, a measure widely employed in quantum information theory. By introducing certain constraints and the ``minimum relative entropy'' hypothesis, we can determine the shape of the structure function in the intermediate-$x$ region, which is intimately connected with…

Glassy interphases reinforce elastomeric nanocomposites by enhancing percolation-driven volume expansion under strain
Pierre Kawak, Harshad Bhapkar, David S. Simmons
https://arxiv.org/abs/2509.04755

Glassy interphases reinforce elastomeric nanocomposites by enhancing percolation-driven volume expansion under strain
For nearly a century, introduction of nanoparticles to elastomers has yielded extraordinarily tough nanocomposites that are critical to technologies from actuators to tires. The mechanisms by which this reinforcement occurs have nevertheless remained a central open question in material science. One widely debated hypothesis posits that strong interactions between polymer and particles induce "glassy bridges" that cement particles into a cohesive percolating network that resists elongation. Here…

Learning with Episodic Hypothesis Testing in General Games: A Framework for Equilibrium Selection
Ruifan Yang, Manxi Wu
https://arxiv.org/abs/2507.23149 https://

Learning with Episodic Hypothesis Testing in General Games: A Framework for Equilibrium Selection
We introduce a new hypothesis testing-based learning dynamics in which players update their strategies by combining hypothesis testing with utility-driven exploration. In this dynamics, each player forms beliefs about opponents' strategies and episodically tests these beliefs using empirical observations. Beliefs are resampled either when the hypothesis test is rejected or through exploration, where the probability of exploration decreases with the player's (transformed) utility. In general fin…

Highly Interactive Testing for Uninterrupted Development Flow
Andrew Tropin
https://arxiv.org/abs/2508.02176 https://arxiv.org/pdf/2508.02176

Highly Interactive Testing for Uninterrupted Development Flow
Highly interactive development environments (HIDEs) enable uninterrupted development flow through continuous program evolution and rapid hypothesis checking. However, traditional testing approaches -- typically executed separately via CLI -- isolate tests from HIDE tooling (interactive debuggers, value and stack inspectors, etc.) and introduce disruptive delays due to coarse execution granularity and lack of runtime context. This disconnect breaks development flow by exceeding critical attentio…

On Unconditionality and Higher-Order Schreier Unconditionality
Mark Shiliaev
https://arxiv.org/abs/2510.02783 https://arxiv.org/pdf/2510.02783

On Unconditionality and Higher-Order Schreier Unconditionality
Let $X$ be a Banach space, $(e_n)_{n=1}^\infty$ be its basis, and $S_α$ be a Schreier family of order alpha. We introduce Condition A which is a weaker version of the Continuum Hypothesis. Granted Condition A, we show that if the basis $(e_n)$ is $S_α$-unconditional for every countable ordinal alpha, then it is unconditional.

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
Federico Tiblias, Irina Bigoulaeva, Jingcheng Niu, Simone Balloccu, Iryna Gurevych
https://arxiv.org/abs/2510.01025

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
The linear representation hypothesis states that language models (LMs) encode concepts as directions in their latent space, forming organized, multidimensional manifolds. Prior efforts focus on discovering specific geometries for specific features, and thus lack generalization. We introduce Supervised Multi-Dimensional Scaling (SMDS), a model-agnostic method to automatically discover feature manifolds. We apply SMDS to temporal reasoning as a case study, finding that different features form var…

Mechanisms of Matter: Language Inferential Benchmark on Physicochemical Hypothesis in Materials Synthesis
Yingming Pu, Tao Lin, Hongyu Chen
https://arxiv.org/abs/2509.25281 http…

Mechanisms of Matter: Language Inferential Benchmark on Physicochemical Hypothesis in Materials Synthesis
The capacity of Large Language Models (LLMs) to generate valid scientific hypotheses for materials synthesis remains largely unquantified, hindered by the absence of benchmarks probing physicochemical logics reasoning. To address this, we introduce MatterMech, a benchmark for evaluating LLM-generated hypotheses across eight nanomaterial synthesis domains. Our analysis reveals a critical disconnect: LLMs are proficient in abstract logic yet fail to ground their reasoning in fundamental physicoch…

Perpetua: Multi-Hypothesis Persistence Modeling for Semi-Static Environments
Miguel Saavedra-Ruiz, Samer B. Nashed, Charlie Gauthier, Liam Paull
https://arxiv.org/abs/2507.18808

Perpetua: Multi-Hypothesis Persistence Modeling for Semi-Static Environments
Many robotic systems require extended deployments in complex, dynamic environments. In such deployments, parts of the environment may change between subsequent robot observations. Most robotic mapping or environment modeling algorithms are incapable of representing dynamic features in a way that enables predicting their future state. Instead, they opt to filter certain state observations, either by removing them or some form of weighted averaging. This paper introduces Perpetua, a method for mo…

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
Federico Tiblias, Irina Bigoulaeva, Jingcheng Niu, Simone Balloccu, Iryna Gurevych
https://arxiv.org/abs/2510.01025

Shape Happens: Automatic Feature Manifold Discovery in LLMs via Supervised Multi-Dimensional Scaling
The linear representation hypothesis states that language models (LMs) encode concepts as directions in their latent space, forming organized, multidimensional manifolds. Prior efforts focus on discovering specific geometries for specific features, and thus lack generalization. We introduce Supervised Multi-Dimensional Scaling (SMDS), a model-agnostic method to automatically discover feature manifolds. We apply SMDS to temporal reasoning as a case study, finding that different features form var…