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How LLMs Might Think
从哲学与认知科学角度探讨大语言模型是否可能真正具备思维，融合AI前沿与心灵哲学。
arXiv:2604.09674v2 Announce Type: replace Abstract: Do large language models (LLMs) think? Daniel Stoljar and Zhihe Vincent Zhang have recently develo…
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Comparing Semantic Navigation in Humans and Large Language Models using Natural Language Processing
用NLP对比人类与LLM的语义导航能力，揭秘AI认知机制的新视角。
arXiv:2607.12195v1 Announce Type: new Abstract: Semantic memory retrieval can be conceptualized as navigation through conceptual space. We compared se…
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Confident but Conflicted: Internal Uncertainty and Cognitive Dissonance Resolution in LLMs
大语言模型看似自信输出时，内部却在处理认知失调，这篇论文揭示了这种矛盾心理机制。
arXiv:2606.22633v1 Announce Type: new Abstract: Large language models (LLMs) frequently encounter inputs that disagree with their prior outputs, throu…
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Factual Retrieval in LLMs Is a Redundant, Distributed and Non-Contiguous Process
揭秘LLM事实检索机制：冗余、分布式、非连续的计算过程，挑战传统认知。
arXiv:2606.21345v1 Announce Type: new Abstract: Large language models (LLMs) store and recall factual knowledge, yet the precise mechanism of how enti…
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LLM and Human Modes of Representation
探讨大语言模型与人类表征模式的差异，从认知科学视角剖析AI理解能力
arXiv:2606.21616v1 Announce Type: new Abstract: Much work on the cognitive foundations of AI has focussed on comparisons between the ways in which Lar…
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The Metanym Game: A Self-Contained, Self-Consistent LLM Peer-Community Benchmark for Structural Intelligence
无需预设数据、LLM自主生成内容的结构智能评测新方法——类比测试进入可证伪时代
arXiv:2606.21008v1 Announce Type: cross Abstract: The metanym game is a competitive word game for LLMs that measures structural intelligence against e…
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The AI architecture "attention" can't hold attention
GPT-5等大模型在简单的人类注意力测试中败下阵来，Stroop效应暴露出AI注意力架构的致命短板。
Article URL: https://scitechdaily.com/even-gpt-5-failed-this-human-attention-test/ Comments URL: https://news.ycombinator.com/item?id=48626330 Points:…
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Reasoning as Pattern Matching: Shared Mechanisms in Human and LLM Everyday Reasoning
探讨人类与LLM日常推理中共享的模式匹配机制，挑战“真正推理”与“模式匹配”的二分法
arXiv:2606.13607v1 Announce Type: new Abstract: When large language models (LLMs) fail to generalize or make haphazard errors in reasoning, it is ofte…
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When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About?
揭示AI心理理论研究中的概念混淆：模式匹配不等于真正认知，别再误读“机器有思维”了。
arXiv:2510.02660v2 Announce Type: replace-cross Abstract: When researchers claim AI systems possess ToM or mental models, they are fundamentally discu…
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Emergent Language as an Approach to Conscious AI
探讨涌现语言如何作为实现有意识AI的新路径，融合语言学与认知科学前沿，挑战传统AI意识理论。
arXiv:2606.06380v1 Announce Type: cross Abstract: The question of whether artificial systems can be conscious remains open, in part because existing a…
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Embodied Cognition and Agentic AI
从具身认知探讨智能体AI的发展，揭示身体与环境交互对人工智能的深刻影响
Article URL: https://lemire.me/blog/2026/05/28/embodied-cognition-and-agentic-ai/ Comments URL: https://news.ycombinator.com/item?id=48394638 Points: …
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Noisy memory encoding explains negative polarity illusions
用噪音记忆编码模型揭示“负极性词”语法幻觉的认知根源，颠覆传统语法判断认知
arXiv:2606.04340v1 Announce Type: new Abstract: A sentence like "The authors that no critics recommended have ever received acknowledgment for a best-…
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Revisiting Anthropomorphic Reflection Markers in Large Language Model Reasoning
重新审视LLM推理中的拟人化反思标记，揭示模型认知行为新视角
arXiv:2605.28305v1 Announce Type: cross Abstract: Large Language Models (LLMs) often produce explicit reflective traces during complex reasoning, acco…
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Post-training makes large language models less human-like
后训练阶段会让大语言模型表现得更不像人类，颠覆了传统认知。
arXiv:2605.07632v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as surrogates for human participants, but…
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Hypothesis Generation and Inductive Inference in Children and Language Models
儿童与语言模型在假设生成和归纳推理上的相似性，揭示人类与AI在不确定性下构建心理模型的计算原理
arXiv:2605.24528v1 Announce Type: new Abstract: Real world decision-making requires constructing mental models under uncertainty over evidence, over t…
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"Subligence" – proposed coinage for LLM "intelligence"
一个新词汇「subligence」被提出，精准区分AI的“类智能”与人类智能，引发对LLM本质的思考。
Call me a snowflake, but I propose that those of us who don't believe that AI is actually intelligence look for a term to refer to its "thinking" that…
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Tracing the ongoing emergence of human-like reasoning in Large Language Models
聚焦LLM推理能力的演化路径，揭示类人推理如何在大模型中涌现
arXiv:2605.21299v1 Announce Type: new Abstract: Humans effortlessly go beyond literal meanings: If you mow the lawn, I will give you fifty dollars, is…
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Interoceptive Divergence in Aesthetic Evaluation and Implications for Human-AI Alignment
从内感受差异切入审美评价，揭示人类与AI对齐的新维度。
arXiv:2605.18759v1 Announce Type: cross Abstract: Artificial intelligence (AI), exemplified by large language models (LLMs), is rapidly approaching an…
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Artificial Phantasia: Emergent Mental Imagery in Large Language Models
颠覆认知：大模型能否仅靠语言产生视觉意象？研究揭示新可能。
arXiv:2509.23108v2 Announce Type: replace-cross Abstract: Can visual imagery be driven solely by language? This idea goes against cognitive science's …