Do Language Models Have Semantics? On the Five Standard Positions
Anders Søgaard
摘要
We identify five positions on whether large language models (LLMs) and chatbots can be said to exhibit semantic understanding. These positions differ in whether they attribute semantics to LLMs and/or chatbots trained on feedback, what kind of semantics they attribute (inferential or referential), and in virtue of what they attribute referential semantics (internal or external causes). This allows for 2 4 = 16 logically possible positions, only five of which have been argued for. Based on a pairwise comparison of these five positions, we conclude that the better theory of semantics in large language models is, in fact, a sixth combination: Both large language models and chatbots have inferential and referential semantics, grounded in both internal and external causes.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper8
- Climbing towards NLU: On Meaning, Form, and Understanding in the Age of DataEmily M. Bender, Alexander KollerACL 2020 · 被引用 914 次
- Language Models Represent Space and TimeWes Gurnee, Max TegmarkICLR 2024 · 被引用 303 次
- The Quantization Model of Neural ScalingEric J. Michaud, Ziming Liu, Uzay Girit, Max TegmarkNeurIPS 2023 · 被引用 179 次
- Harnessing the Universal Geometry of EmbeddingsRishi D. Jha, Collin Zhang, Vitaly Shmatikov, John X. MorrisNeurIPS 2025 · 被引用 69 次
- Non-Vacuous Generalization Bounds for Large Language ModelsSanae Lotfi, Marc Anton Finzi, Yilun Kuang, Tim G. J. Rudner 等ICML 2024 · 被引用 49 次
相关 Paper
- LLM-Guided Semantic Relational Reasoning for Multimodal Intent RecognitionQianrui Zhou, Hua Xu, Yifan Wang, Xinzhi Dong 等EMNLP 2025
- Large Language Models: The Need for Nuance in Current Debates and a Pragmatic Perspective on UnderstandingBram van Dijk, Tom Kouwenhoven, Marco Spruit, Max Johannes van DuijnEMNLP 2023 · 被引用 12 次
- How LLMs Comprehend Temporal Meaning in Narratives: A Case Study in Cognitive Evaluation of LLMsKarin de Langis, Jong Inn Park, Andreas Schramm, Bin Hu 等ACL 2025
- Supporting Effective Goal Setting with LLM-Based ChatbotsMichel Schimpf, Sebastian Maier, Anton Wyrowski, Lara Christoforakos 等CHI 2026 · 被引用 2 次
- Towards Understanding the Characteristics of Code Generation Errors Made by Large Language ModelsZhijie Wang, Zijie Zhou, Da Song, Yuheng Huang 等ICSE 2025 · 被引用 12 次
