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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. COMMENTARY · Mastodon — fosstodon.org Polski(PL) · · [3 sources]

    Linguistic Features - What You Need to Know Before Understanding How LLMs Think https:// gruszka.dev/cechy-jezykowe-a-l lm.html # llm # ai # linguistics # nlp # linguis

    This cluster explores the fundamental concepts behind how Large Language Models (LLMs) process and understand text. It delves into the journey from simple word counting to complex vector representations, touching upon linguistic features essential for comprehending LLM thought processes. The discussion also examines semiotics and its relevance, or lack thereof, to LLMs, referencing key figures in linguistic theory. AI

    IMPACT Explores the theoretical underpinnings of LLMs, offering insights into their text processing capabilities and linguistic limitations.

  2. TOOL · arXiv cs.CL English(EN) ·

    The meaning of prompts and the prompts of meaning: Semiotic reflections and modelling

    This paper presents a theoretical framework for understanding prompts in large language models (LLMs) through the lens of semiotics. It proposes that prompting is not merely a technical input but a dynamic communicative and epistemic act involving sign formation and interpretation. By applying Peirce's semiotic models, the research suggests that LLMs act as semiotic resources that co-construct meaning, thereby reshaping how knowledge is organized and accessed in digital environments. AI

    IMPACT Reframes understanding of LLM interaction, potentially influencing future AI design and human-AI communication strategies.