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Lorde says AI glasses are “not sexy”
Singer-songwriter Lorde expressed skepticism about AI glasses during a performance, stating they are not appealing and make it harder to discern reality.
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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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HABIB_TAZ at SemEval-2026 Task 11: Disentangling Formal Logic from Content via Synthetic Training and Multi-Objective Optimization
The HABIB_TAZ system uses synthetic training and multi-objective optimization to help language models separate formal logic from real-world content biases.
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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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Automated identification of Ichneumonoidea wasps via YOLO-based deep learning: Integrating HiresCam for Explainable AI
Researchers have developed a deep learning framework using YOLO and explainable AI techniques to automate the taxonomic identification of parasitoid wasps.
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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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Knowing You at First Glance: Inferring Apparent Personality from Faces
A new study explores methods for AI agents to infer personality traits from facial images to improve human-robot interaction.
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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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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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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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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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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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Comparing Socio-technical Design Principles with Guidelines for Human-centered AI
This paper compares human-centered AI guidelines with traditional socio-technical design principles to propose updated heuristics for AI system integration.
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PHITSBench: an execution-scored benchmark for AI-assisted PHITS radiation-transport input generation using natural language
PHITSBench is a new execution-scored benchmark designed to evaluate AI performance in generating inputs for the PHITS radiation-transport simulation code.
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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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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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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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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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WrAFT: a Modularized Automated Writing Evaluation System for Argumentative Essays
WrAFT is a modular automated writing evaluation system designed to provide scoring and feedback for argumentative essays using various large language models.
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Decision Making Needs Uncertainty Quantification [Lecture Notes]
These lecture notes examine the theoretical relationship between uncertainty quantification and effective decision-making in autonomous agents.