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arXiv:2603.03303v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to simulate how specific users respond to a given context, enabling more user-centric …
arXiv:2603.03304v1 Announce Type: cross Abstract: We present a concise architecture for joint training on sentences and structured data while keeping knowledge and language representations separable. …
arXiv:2603.03305v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate executable outputs, JSON objects, and API calls, where a single syntax …
arXiv:2603.03306v1 Announce Type: cross Abstract: Recently presented Token-Oriented Object Notation (TOON) aims to replace JSON as a serialization format for passing structured data to LLMs …
arXiv:2603.03307v1 Announce Type: cross Abstract: Epistemic Network Analysis (ENA) is a method for investigating the relational structure of concepts in text by representing co-occurring concepts …
arXiv:2603.03308v1 Announce Type: cross Abstract: How does the conversational past of large language models (LLMs) influence their future performance? Recent work suggests that LLMs are …
arXiv:2603.03312v1 Announce Type: cross Abstract: Decoding natural language from non-invasive EEG signals is a promising yet challenging task. However, current state-of-the-art models remain constrained by …
arXiv:2603.03313v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit a significant "embodiment gap", where their text-based representations fail to align with human sensorimotor experiences. …
arXiv:2603.03314v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable and steadily improving performance across a wide range of tasks. However, LLM performance …
arXiv:2603.03315v1 Announce Type: cross Abstract: Internet memes are a powerful form of online communication, yet their nature and reliance on commonsense knowledge make toxicity detection …
arXiv:2603.03316v1 Announce Type: cross Abstract: Most sign language recognition research relies on Transfer Learning (TL) from vision-based datasets such as ImageNet. Some extend this to …
arXiv:2603.03318v1 Announce Type: cross Abstract: Recent advances in Natural Language Processing have been predominantly driven by transformer-based architectures, which rely heavily on self-attention mechanisms to …