ciwGAN and fiwGAN models trained on isolated words spontaneously generate concatenated multi-word outputs and display early compositionality precursors.
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Analysis of 500k ChatGPT logs shows over one-third of conversations generate fiction, dominated by power users with repetitive and niche patterns.
Defines memetic capture as AI-driven cultural disempowerment and outlines the CPGF policy architecture combining metrics, democratic assemblies, pluralistic standards, and transnational coordination.
LLM societies in Nomic show non-monotonic collective adaptation peaking at mid-scales, with smaller models rule-inert and larger ones restrictive.
3D-VLA is a new embodied foundation model that uses a 3D LLM plus aligned diffusion models to generate future images and point clouds for improved reasoning and action planning in 3D environments.
Multi-source prediction-powered inference aggregates multiple pseudo-labeled datasets via weights chosen to minimize asymptotic confidence-region volume, with asymptotic normality and comparisons to single-source and target-only baselines shown for both homogeneous and heterogeneous (covariate/domai
Presents a new annotated resource of 1,482 tweets for enthymeme detection that studies label variation instead of eliminating it, with preliminary evidence that disagreement-aware training improves model performance.
Agentic Redux claims provably correct LLM agent executions on suitable domains via typed lambda calculus with full decision logging, demonstrated on healthcare compliance and security disclosure with supporting code.
Iterated learning theory predicts and LLM experiments confirm non-monotonic compositionality during self-training, reframing model collapse as cultural transmission with matching human regularization patterns.
Information defined as maximum-caliber deviation derives IIT 3.0 cause-effect repertoires from constrained entropy maximization and equates to prediction error under CLT and LDT.
Transportability methods can transport causal effects from experimental samples to broader target populations in software engineering by leveraging observational data to improve external validity.
A critical incident technique study with 142 participants identifies mechanisms by which games create or block agender euphoria and supplies empirically grounded design criteria for gender-neutral play.
ABot-M0 unifies heterogeneous robot data into a 6-million-trajectory dataset and introduces Action Manifold Learning to predict stable actions on a low-dimensional manifold using a DiT backbone.
An unsupervised method detects domain shifts via localized density anomaly search in feature space, attributes the shift to a minimal subspace, and extracts balanced subsets from two unlabeled datasets.
CaloArt achieves top FPD, high-level, and classifier metrics on CaloChallenge datasets 2 and 3 while keeping single-GPU generation at 9-11 ms per shower by combining large-patch tokenization, x-prediction, and conditional flow matching.
The method uses multi-view diffusion priors and action manifold learning to resolve depth ambiguity and improve action prediction in VLA robotic manipulation models, reporting higher success rates than baselines on LIBERO, RoboTwin, and real-robot tasks.
Neo, a cGAN, super-resolves HSC images to HST-like quality and improves galaxy morphological parameter accuracy by factors of 2-10.
NaviGNN combines RL and GNNs in multi-agent simulations to achieve 7.8-8.4 minute average commutes, over 89% satisfaction, and above 91% reachability in extreme urban morphologies.
Empirical finance is limited to ex post causal inference because self-reference in markets makes unidirectional causation unstable or fallacious.
A late-fusion gradient-boosting pipeline with LLM semantic features is submitted to the EXIST 2026 lab for sexism identification in memes and videos, showing mixed generalization from development to test data.
citing papers explorer
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Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks
ciwGAN and fiwGAN models trained on isolated words spontaneously generate concatenated multi-word outputs and display early compositionality precursors.
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AI Fiction in the Wild
Analysis of 500k ChatGPT logs shows over one-third of conversations generate fiction, dominated by power users with repetitive and niche patterns.
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Memetic Capture: A Pluralistic Policy Framework for Governing AI-Driven Cultural Disempowerment
Defines memetic capture as AI-driven cultural disempowerment and outlines the CPGF policy architecture combining metrics, democratic assemblies, pluralistic standards, and transnational coordination.
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Scale-Dependent Collective Adaptation in Self-Amending LLM Societies: A Cross-Family Study of Emergent Governance
LLM societies in Nomic show non-monotonic collective adaptation peaking at mid-scales, with smaller models rule-inert and larger ones restrictive.
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3D-VLA: A 3D Vision-Language-Action Generative World Model
3D-VLA is a new embodied foundation model that uses a 3D LLM plus aligned diffusion models to generate future images and point clouds for improved reasoning and action planning in 3D environments.
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Multi-Source Prediction-Powered Inference
Multi-source prediction-powered inference aggregates multiple pseudo-labeled datasets via weights chosen to minimize asymptotic confidence-region volume, with asymptotic normality and comparisons to single-source and target-only baselines shown for both homogeneous and heterogeneous (covariate/domai
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A Resource for Enthymeme Detection in Controversial Political Discourse
Presents a new annotated resource of 1,482 tweets for enthymeme detection that studies label variation instead of eliminating it, with preliminary evidence that disagreement-aware training improves model performance.
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Provably Auditable and Safe LLM Agents from Human-Authored Ontologies
Agentic Redux claims provably correct LLM agent executions on suitable domains via typed lambda calculus with full decision logging, demonstrated on healthcare compliance and security disclosure with supporting code.
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Model Collapse as Cultural Evolution
Iterated learning theory predicts and LLM experiments confirm non-monotonic compositionality during self-training, reframing model collapse as cultural transmission with matching human regularization patterns.
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Information as Maximum-Caliber Deviation: A bridge between Integrated Information Theory and the Free Energy Principle
Information defined as maximum-caliber deviation derives IIT 3.0 cause-effect repertoires from constrained entropy maximization and equates to prediction error under CLT and LDT.
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Towards Improving the External Validity of Software Engineering Experiments with Transportability Methods
Transportability methods can transport causal effects from experimental samples to broader target populations in software engineering by leveraging observational data to improve external validity.
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Radical Gender Neutrality: Agender Euphoria in Gaming and Play Experiences
A critical incident technique study with 142 participants identifies mechanisms by which games create or block agender euphoria and supplies empirically grounded design criteria for gender-neutral play.
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ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
ABot-M0 unifies heterogeneous robot data into a 6-million-trajectory dataset and introduces Action Manifold Learning to predict stable actions on a low-dimensional manifold using a DiT backbone.
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Unsupervised Domain Shift Detection with Interpretable Subspace Attribution
An unsupervised method detects domain shifts via localized density anomaly search in feature space, attributes the shift to a minimal subspace, and extracts balanced subsets from two unlabeled datasets.
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CaloArt: Large-Patch x-Prediction Diffusion Transformers for High-Granularity Calorimeter Shower Generation
CaloArt achieves top FPD, high-level, and classifier metrics on CaloChallenge datasets 2 and 3 while keeping single-GPU generation at 9-11 ms per shower by combining large-patch tokenization, x-prediction, and conditional flow matching.
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Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation
The method uses multi-view diffusion priors and action manifold learning to resolve depth ambiguity and improve action prediction in VLA robotic manipulation models, reporting higher success rates than baselines on LIBERO, RoboTwin, and real-robot tasks.
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Photometric Super-Resolution for Improving Galaxy Morphological Measurements using Conditional Generative Adversarial Networks
Neo, a cGAN, super-resolves HSC images to HST-like quality and improves galaxy morphological parameter accuracy by factors of 2-10.
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NaviGNN: Multi-Agent Reinforcement Learning and Graph Neural Network for Sustainable Mobility in Futuristic Smart Cities
NaviGNN combines RL and GNNs in multi-agent simulations to achieve 7.8-8.4 minute average commutes, over 89% satisfaction, and above 91% reachability in extreme urban morphologies.
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Epistemic Limits of Empirical Finance: Causal Reductionism and Self-Reference
Empirical finance is limited to ex post causal inference because self-reference in markets makes unidirectional causation unstable or fallacious.
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Multimodal Sexism Identification and Characterization using Large Language Models and Gradient Boosting
A late-fusion gradient-boosting pipeline with LLM semantic features is submitted to the EXIST 2026 lab for sexism identification in memes and videos, showing mixed generalization from development to test data.