Residual-Space Evolutionary Optimization via Flow-based Generative Models
Residual-Space Evolutionary Optimization via Flow-based Generative Models This paper introduces a new framework for editing data—such as images or scientific...
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Residual-Space Evolutionary Optimization via Flow-based Generative Models This paper introduces a new framework for editing data—such as images or scientific...
Implicit Semantic-aware Communication Based on Hypergraph Reasoning introduces a new framework called HISR to improve how communication systems understand an...
PhysDrift: Bridging the Embodiment Gap in Humanoid Co-Speech Motion Generation Humanoid robots are increasingly expected to interact with humans using natura...
Beyond Accuracy: Measuring Logical Compliance of Predictive Models In high-stakes fields like healthcare, finance, and autonomous systems, machine learning m...
Confidence-Aware Automated Assessment of Student-Drawn Scientific Models In science education, students often create drawings to demonstrate their understand...
RACL: Reasoning-Agent Control Layers for Continuous Metaheuristic Learning Many companies rely on metaheuristic optimizers to solve complex logistics and rou...
What Do Safety-Aligned LLMs Learn From Mixed Compliance Demonstrations? This research investigates how large language models (LLMs) interpret "compliance dem...
Leveraging systems' non-linearity to tackle the scarcity of data in the design of Intelligent Fault Diagnosis Systems This paper introduces a new method for...
Navigating Unreliable Parametric and Contextual Knowledge: Explicit Knowledge Conflict Resolution for LLM Inference Large language models (LLMs) often strugg...
QMFOL: Benchmarking Large Language Model Reasoning via Quantifiable Monadic First-Order Logic Test Case Generation As Large Language Models (LLMs) continue t...
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