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arXiv:2603.19278v1 Announce Type: cross Abstract: Modern Transformer-based models frequently suffer from miscalibration, producing overconfident predictions that do not reflect true empirical frequencies. This work investigates …
arXiv:2603.19280v1 Announce Type: cross Abstract: The rapid advancements in large language models and generative artificial intelligence (AI) capabilities are making their broad application in the …
arXiv:2603.19281v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a widely adopted approach for enhancing LLMs in scenarios that demand extensive factual knowledge. …
arXiv:2603.19282v1 Announce Type: cross Abstract: In many real-world applications, large language models (LLMs) operate as independent agents without interaction, thereby limiting coordination. In this setting, …
arXiv:2603.19284v1 Announce Type: cross Abstract: With the rapid advancement of large language models (LLMs), LLM-based heuristic search methods have demonstrated strong capabilities in automated algorithm …
arXiv:2603.19286v1 Announce Type: cross Abstract: Predicting stock prices presents challenges in financial forecasting. While traditional approaches such as ARIMA and RNNs are prevalent, recent developments …
arXiv:2603.19288v1 Announce Type: cross Abstract: Portfolio construction traditionally relies on separately estimating expected returns and covariance matrices using historical statistics, often leading to suboptimal allocation …
arXiv:2603.19289v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have gained popularity as a means of scaling the capacity of large language models (LLMs) while maintaining …
arXiv:2603.19290v1 Announce Type: cross Abstract: Integrating Spiking Neural Networks (SNNs) with Transformer architectures offers a promising pathway to balance energy efficiency and performance, particularly for …
arXiv:2603.19291v1 Announce Type: cross Abstract: As regression is a widely studied problem, many methods have been proposed to solve it, each of them often requiring …
arXiv:2603.19249v1 Announce Type: new Abstract: Healthcare question-answering (QA) systems face a persistent challenge: users submit queries with spelling errors at rates substantially higher than those …
arXiv:2603.19250v1 Announce Type: new Abstract: Evaluating language models in streaming environments is critical, yet underexplored. Existing benchmarks either focus on single complex events or provide …
