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Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data This research investigates how language diffusion models—specifically Un...
Persuadability and LLMs as Legal Decision Tools As Large Language Models (LLMs) are increasingly considered for roles as legal assistants or even first-insta...
This paper explores how neural assemblies—groups of neurons that fire together and strengthen through repeated co-activation—can learn the direction of causa...
This study investigates the behavioral patterns associated with learned helplessness (LH) in students using mathematics tutoring systems.
ViCrop-Det: Spatial Attention Entropy Guided Cropping for Training-Free Small-Object Detection Transformer-based object detectors often struggle to identify...
Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework introduces a new way to design time series mod...
Rule-based High-Level Coaching for Goal-Conditioned Reinforcement Learning in Search-and-Rescue UAV Missions Under Limited-Simulation Training This paper int...
Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields This research addresses the challenge of autonomous robots or...
Hierarchical Multi-Persona Induction from User Behavioral Logs: Learning Evidence-Grounded and Truthful Personas This paper introduces a new framework design...
Evaluating Strategic Reasoning in Forecasting Agents Forecasting benchmarks often provide leaderboards showing which AI models are most accurate, but they ra...
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