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Structured Thoughts For Improved Reasoning And Context Pruning
A new framework called Structured Thoughts organizes large language model reasoning into distinct blocks to enhance efficiency and context management.
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Feedback-Coupled Memory Systems in Continuous Time
This research formalizes the Feedback-Coupled Memory Systems architecture in continuous time, defining agent updates through decentralized economic principles.
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Beyond Bayesian Nash: Learning Minimax-Regret Equilibria for Adversarial Team Games under Asymmetric Information
This research introduces a method for learning minimax-regret equilibria in adversarial team games with asymmetric information to counter deceptive opponent strategies.
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Towards Objective Dysgraphia Detection: A Multi-Branch Deep Learning Approach for Online Handwriting Analysis
Researchers developed a deep learning-based approach to analyze online handwriting for more objective and efficient dysgraphia detection in children.
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Physics-Informed Structure Anchoring With Capture-Aware Prototype Calibration for Cross-Environment RF Fingerprinting
This study proposes a physics-informed framework to improve the robustness of radio frequency fingerprinting models across changing physical environments.
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Data-Driven Forward and Inverse Modeling of V-Beam Thermal Sensors
This paper introduces a machine learning framework to optimize the geometric design of V-beam thermal sensors under specific temperature and stress constraints.
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SupplyNetPy: An Open-Source Python Library for High-Fidelity Modeling and Simulation of Arbitrary Supply Chain and Inventory Networks
The open-source Python library SupplyNetPy enables high-fidelity modeling and discrete-event simulation of complex supply chain and inventory networks.
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Enhancing Query Efficiency for d-DNNF Representations Through Preprocessing
The paper explores preprocessing techniques to optimize query efficiency for propositional formulas represented in conjunctive normal form.
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Incremental Transformer for Surrogate-Based Inverse Design of Geopolymer Mixtures
This paper proposes a topology-aware surrogate framework using an Incremental Transformer to optimize geopolymer mixture designs under physical constraints.
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AI YOU Town: Make Friends and Money with Your Digital Twin
The AI YOU framework uses Bayesian updating and prompting to continuously update a user's personality profile across 22 dimensions for digital twin applications.
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Meta enters the crowded AI coding battle with Muse Spark 1.1
Meta has launched Muse Spark 1.1, an AI coding tool designed to manage large agentic workloads, debug code, and assist with software migrations.
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Flout at Your Own Risk: LLMs Struggle with Pragmatic Cooperativity Under Epistemic Asymmetry
The study investigates the limitations of LLMs in collaborative settings, specifically their difficulty in managing pragmatic communication when information is asymmetrically distributed.
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Heterogeneous Element-Aware Cross-Version Differencing of Scientific Documents via Layout-Aware Alignment and Structure-Aware Reasoning
A new approach for comparing scientific document versions integrates layout-aware alignment and structural reasoning to handle complex elements like tables and formulas.
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When AI Blurs the Boundaries of Contribution: An Empirical Study of Authorship Calibration
This study examines how users perceive their own authorship when collaborating with generative AI tools.
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CrimeNER Demo: Named-Entity Recognition in the Crime Domain
A new platform called CrimeNER Demo has been introduced to facilitate named-entity recognition and classification of crime-related information in documents.
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Man, Machine, and Masterpiece: Artistic Ownership in the AI Era
Researchers developed a tool to quantify human versus AI contributions in creative works to address ongoing debates regarding artistic ownership.
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Concept-Guided Spatial Regularization for World Models in Atari Pong
Researchers evaluated the performance of five prominent world-model agents in Atari Pong to better understand their isolated capabilities.
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ARMOR: Stabilizing On-Policy LLM RL with Off-Policy Anchor Samples
The ARMOR framework introduces off-policy anchor samples to stabilize reinforcement learning in large language models and prevent over-optimization.
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The Cross-Architecture Substrate: A Domain-Transcendent, Calibration-Surviving Geometric Invariant of Modern Vision Encoders
A study reveals that diverse modern vision encoders converge toward a shared sixteen-dimensional geometric structure, termed the cross-architecture substrate, regardless of their training objectives.
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Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network
This research proposes a model for optimizing power and channel performance in magnetic inductive cellular networks used in underground environments.
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Explaining Process Control Optimisation Recommendations via GradientSHAP and Implicit Differentiation
Researchers propose a method to improve the interpretability of automated industrial process control recommendations using gradient-based explanation techniques.
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Multi-Scale ViT Inference with Habitat-Fit Priors and kNN Retrieval for Multi-Species Plant Identification
A multi-scale vision transformer approach is detailed for identifying multiple plant species in high-resolution photographs using limited training data.
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When Does Restricting a Coding Agent to execute_code Help? A Regime $\times$ Agent-Design Ablation
This study performs a comparative analysis of different code-execution environments to determine their impact on the performance of AI coding agents.
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MG$^2$-RAG: Multi-Granularity Graph for Multimodal Retrieval-Augmented Generation
MG2-RAG is a proposed multimodal retrieval-augmented generation framework that uses multi-granularity graphs to improve reasoning and preserve fine-grained visual data.