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HN 二十年,最值得读的论文。

从 Hacker News 2006 年以来的全部投稿里,挑出链接本身就是论文的帖子:arXiv、期刊、会议论文、技术报告。每篇附中文标题,讨论最热的那些再加上中文导读和高赞评论翻译。

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编辑精选里 HN 讨论最热的 30 篇,每篇都有中文导读。不知道从哪读起,就从这里开始。

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点柱子按年份筛选。注:源数据里 2023 年的帖子分数记录不全,2026 年尚未过完,这两年收录偏少。

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    1. 01

      全量扫一遍

      读取 Hacker News 自 2006 年以来的全部 446 万条链接投稿,找出指向 arXiv、期刊、会议、技术报告和学术 PDF 的帖子。

    2. 02

      只留论文本身

      由 AI 逐条判断,剔除介绍论文的新闻、博客和幻灯片,同一篇论文的多次投稿合并计算,并统计它在评论区被引用的次数。

    3. 03

      写导读、译评论

      讨论最热的 1,500 篇配上中文导读,并精选、翻译 HN 高赞评论。导读由 AI 生成,可能有误,请以原文为准。

    神经科学与心理学2024gwern.net

    语言主要是交流工具而非思维工具

    Language is primarily a tool for communication rather than thought

    进阶 · 约 60 分钟读完前置知识:认知神经科学基础、语言学基本概念、脑成像方法常识

    读论文 HN 讨论
    563HN 得分
    468条评论
    2次投稿

    导读

    这篇论文(Fedorenko 等,2024)论证语言的主要功能是交流而非思维:语言既非思考的必要条件也非充分条件,思维可以在不依赖语言的情况下进行。作者结合神经科学与行为证据,指出语言与思考系统在脑中是可分离的。

    HN 关注点:'我们到底用什么思考'这一根本问题,讨论焦点集中在个体内心体验的巨大差异(有无内心独白)以及 LLM 的成功是否反过来证明思维依赖语言。

    关键词 语言与思维内心独白认知科学LLM

    HN 评论精选

    这几条评论里:支持 1 质疑 1 补充 1 亲历 1

    补充个体思维体验差异巨大,多数人误以为他人和自己一样

    每次想到这两个事实我都震惊:人们的思维体验截然不同,而我们都暗自以为别人和自己一样。我几乎没有强烈的内心独白,所以自然觉得思考不太依赖语言;但很多人完全用语言思考,这在我看来难以置信,反过来他们也这么看我。更离奇的是有人回忆词语时会把它'看'成文字。威斯康星大学有个有趣的测试,可以看看你有多'怪'。

    benrutter查看英文原文

    It absolutely melts my mind every time I come across the two facts that: - People experience their thoughts very differently - We all secretly believe that deep down, everyone experiences thought like we do. I've never really had a strong internal monologue when thinking, so my assumption would always be that of course, thinking isn't very linguistic (even if we can use it as a tool while thinking). It seems like there's a large number of people who experience their thought exclusively as language. That sounds absolutely nuts to me, but I've heard people say the exact same in reverse. Even more fringe is that there's a sizable number of people who when thinking about words (i.e. remembering names) visualize their words as text. What!? I can't imagine that anymore than I can imagine how a jellyfish feels? The University of Wisconsin did a cool study that comes with a fun quiz you can do to see just how much of a wierdo you truly are: https://uwmadison.co1.qualtrics.com/jfe/form/SV_3NMm9yyFsNioVhz

    支持许多概念无词可名,说明思维先于语言;LLM 的局限也印证这一点

    我们思维流中的许多概念并没有对应的词或短语。词语只有在概念足够重要时才被创造出来用于交流,比如日语'積ん読'(买书不读堆积如山)、泰语'น้ำใจ'(不求回报的善意)、中文'关系'。这是支持论文论点的另一条证据。但语言对抽象思考仍极有用,只是并非人人以它为主要思考工具。这也解释了 LLM 空间智能不足等局限——多模态大模型正是用比语言更细粒度的数据来弥补。

    nopinsight查看英文原文

    There are many concepts in our thought stream without a 'word' or even a simple 'phrase' to label them. A word or a common phrase is coined when a concept is sufficiently common and important enough such that someone comes up with a label to communicate the idea succinctly and the label catches on. We, humanity, have words or common phrases to label the vast majority of significant concepts. However, not every concept is accorded such importance in every language. Some common words in other languages without direct translation in English: * 積ん読 (Tsundoku) (Japanese): Buying books and never reading them, just letting them pile up. * น้ำใจ (Nam-jai) (Thai): Literally "water from the heart". Being very nice and helpful without expecting anything back. * 关系 (Guanxi) (Mandarin): Your network of connections that help you get stuff done in life and business. This is perhaps another line of evidence to support the thesis of the article. Make no mistake though: Language is extremely useful for some types of thoughts, especially more abstract ones. Not everyone, however, uses it as their primary tool for thinking. ----- The above also helps explain some limitations of LLMs, such as their inadequate spatial intelligence. Large Multimodal Models (LMMs) start to address these issues by using much more granular data than language alone.

    亲历双语者的亲历:思考基于概念,语言只是可选的'序列化'输出

    我是双语者,总有人问我'用哪种语言思考',但我并不用某种语言思考。我更像是用概念思考,脑中的声音有时配合着用英语或罗马尼亚语'播放'出这些概念的词,但词语并非必需。用开发术语说:我用 struct 思考,然后可选地把它序列化成英/罗语的 JSON。

    calini查看英文原文

    I'm bilingual, people keep asking me what language I think 'in', and I don't think I think _in_ a language. For lack of a better way of describing it, I rather think in concepts, sometimes the voice in my head likes to play along by imagining the words representing those concepts, sometimes in English, sometimes in Romanian, but the words are not necessary. In dev words, I guess I think in structs and then optionally serialize those structs in En/Ro (JSON).

    质疑反方观点:橡皮鸭调试等证据表明语言对复杂思考不可或缺

    我的看法:1) '橡皮鸭调试法'和大量关于口头讲解的研究表明语言对思考至关重要——向物体讲述问题有助于找到解法,口头教别人能记得更牢,考试本身也能促进学习。2) 记忆研究表明'外部化'是记忆的关键,语言(包括内心言语)就是一种外部化,让思想可以被短期和长期记住。没有外部载体的思想更像转瞬即逝的念头,难以支撑复杂的思考。

    justacomment100查看英文原文

    My takes: 1. The existence of “rubber duck debugging”, and a whole bunch of studies on verbally explaining a concept indicate that language is essential for thought. In rubber duck debugging, programmers tell their problem to an object and this is beneficial in finding the solution. There are studies that show when we verbally teach material to someone we remember it better. Also the act of taking a test increases learning and memory, but why should this be if learning is secondary? 2. Everything we know about memory tells us that externality is essential for memorizing something. If there’s nothing visual, aural, or sensory then it is unlikely to be remembered. Language acts as an externality even as inner speech, meaning that thoughts can be said in language (ascribed onto the words) and remembered for short-term and long-term memory. A thought without externality seems more like a passing whim, unrooted in any more permanent mode of cognition and thus liable to be forgotten. I can imagine thinking in visuals, melodies, words, but if there is a kind of thought that isn’t occurring based off of these then it probably can’t be sophisticated.

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    从这篇论文所有 HN 讨论帖的全部评论里整理出来的链接。

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