arXiv Computation and Language
Thinking beyond the anthropomorphic paradigm benefits LLM research
Read the original on arXiv Computation and Language →The Flow has not summarised this story yet — read it at arXiv Computation and Language.
Related stories
arXiv AI
Jun 11
Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!
arXiv:2504. 09762v4 Announce Type: replace Abstract: Intermediate token generation (ITG), where a model produces output before the solution, has become a standard method to improve the performance of language models on reasoning tasks.
arXiv AI
Jun 9
Some hypotheses on how chatbots work in problem-solving-driven conversations. Large Language Models as confirmation of the Innovation Illusion
arXiv:2606. 07722v1 Announce Type: new Abstract: This article offers a perspective on the nature of chatbots as genuine conversation partners when discussing problems in relation to their solutions.
arXiv AI
Sep 12
Some hypotheses on how chatbots work in problem-solution-driven conversations: Large Language Models as confirmation of the Innovation Illusion
The article examines chatbots as partners in problem‑solving conversations, arguing that basic chatbots—comprising a large language model (LLM) and a simple interface—are multifaceted but cannot match human cognitive flexibility. Drawing on Aggregation Dynamics, Cognitive Linguistics, Neuropsychology, and Psychology, the authors describe how LLMs encode artificial metaphorical problem propagations from training data, which only partially imitate human thinking. They conclude that further LLM development will not yield true thinking partners, yet chatbots are widely used, making their understanding socially and politically important.
arXiv AI
Jun 2
Addressing Longstanding Challenges in Cognitive Science with Language Models
arXiv:2511. 00206v3 Announce Type: replace Abstract: Cognitive science faces ongoing challenges in research integration, formalization, conceptual clarity, and other areas, in part due to its multifaceted and interdisciplinary nature.
arXiv AI
Jun 3
A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents
arXiv:2601. 09869v2 Announce Type: replace Abstract: Anthropomorphisation -- the phenomenon whereby non-human entities are ascribed human-like qualities -- has become increasingly salient with the rise of large language model (LLM)-based conversational agents (CAs).
arXiv AI
Jun 3
If LLMs Have Human-Like Attributes, Then So Does Age of Empires II
arXiv:2605. 31514v2 Announce Type: replace-cross Abstract: Much research has been carried out on large language models (LLMs) and LLM-powered agentic workflows.