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arXiv:2604.00130v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting has significantly improved the reasoning capabilities of large language models (LLMs). However, conventional CoT often relies on …
arXiv:2604.01476v1 Announce Type: new Abstract: Reinforcement learning for LLMs is vulnerable to reward hacking, where models exploit shortcuts to maximize reward without solving the intended …
arXiv:2604.01727v1 Announce Type: new Abstract: Forecasting evolving clinical risks relies on intrinsic pathological dependencies rather than mere chronological proximity, yet current methods struggle with coarse …
arXiv:2604.01261v1 Announce Type: new Abstract: Time series forecasting (TSF) is critical across domains such as finance, meteorology, and energy. While extending the lookback window theoretically …
arXiv:2604.00023v1 Announce Type: new Abstract: Basic vocabulary in many Sulawesi Austronesian languages includes forms resisting reconstruction to any proto-form with phonological patterns inconsistent with inherited …
arXiv:2604.00008v1 Announce Type: cross Abstract: As qualitative researchers show growing interest in using automated tools to support interpretive analysis, a large language model (LLM) is …
arXiv:2604.00011v1 Announce Type: cross Abstract: The growing prominence of large language models (LLMs) in daily life has heightened concerns that LLMs exhibit many of the …
arXiv:2604.00281v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded in computer science education through AI-assisted programming tools, yet such workflows often exhibit …
arXiv:2604.01769v1 Announce Type: new Abstract: For multi-input and multi-output (MIMO) channels, the optimal channel estimation (CE) based on linear minimum mean square error (LMMSE) requires …
arXiv:2604.01775v1 Announce Type: new Abstract: Although demand forecasting is a critical component of supply chain planning, actual retail data can exhibit irreconcilable seasonality, irregular spikes, …
arXiv:2604.00239v1 Announce Type: new Abstract: The world's 7,000+ languages vary widely in the availability of resources for NLP, motivating efforts to systematically categorize them by …
arXiv:2604.01595v1 Announce Type: new Abstract: Seizure detection from EEG signals is highly challenging due to complex spatiotemporal dynamics and extreme inter-patient variability. To model them, …