[HN Gopher] Language Model Contains Personality Subnetworks
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       Language Model Contains Personality Subnetworks
        
       Author : PaulHoule
       Score  : 42 points
       Date   : 2026-03-02 15:41 UTC (7 hours ago)
        
 (HTM) web link (arxiv.org)
 (TXT) w3m dump (arxiv.org)
        
       | sarducci wrote:
       | to me this suggests that language strongly influences behavior
        
         | soulofmischief wrote:
         | I think specifically, certain psychological modes require
         | different levels of articulation, and language is one way to
         | get there in a bandwidth-limited system.
         | 
         | See also: https://en.wikipedia.org/wiki/Newspeak
        
           | PaulHoule wrote:
           | People are fascinated by controlling the vocabulary for
           | political purposes but I think it mostly doesn't work.
           | "Illegal Alien" is the exception that proves the rule.
           | 
           | Usually it results in an "equal and opposite backlash". Once
           | they started calling children "Special" in school, "Special"
           | became the ultimate insult.
        
             | D-Machine wrote:
             | It is a wordcel problem, i.e. the belief that language is
             | all there is for modeling reality, even though this is
             | obviously false and has been clearly disproven by decades
             | of research in psychology, cognitive science, and
             | neuroscience. At best we can say that _sometimes_ language
             | has a strong influence on our perceptions of reality.
             | 
             | EDIT: For a neuroscience reference that also argues why the
             | general perspective is obviously false:
             | https://pmc.ncbi.nlm.nih.gov/articles/PMC4874898/. But
             | really, these things ought to be obvious from
             | introspection.
        
               | PaulHoule wrote:
               | Also in my dealing with birds and animals of all sorts
               | I've come to believe that they are very capable in many
               | forms of cognition without the use of language.
               | 
               | There was a fad called "structuralism" that liked to
               | imagine that such and such is "structured like a
               | language" but then when we got a paradigm for language it
               | was one of those "normal science" paradigms that Kuhn
               | warned you about, like you could write papers grounded in
               | the Chomsky theory for a lifetime but it wouldn't help
               | you learn to read Chinese more quickly or speak German
               | without an accent or program a computer to parse tweets.
               | That is, the structure of language is absolutely useless
               | except for writing papers about linguistics -- and the
               | "language instinct" becomes some peripheral that grafts
               | onto an animal but you need the rest of the animal for it
               | to work.
               | 
               | Now LLMs may not be a model for how we do it but they are
               | certainly going to bring back structuralist and "wordcel"
               | positions because they do seem to show, somehow, that
               | "language is all you need" to accomplish whatever it is
               | LLMs accomplish.
        
               | D-Machine wrote:
               | > Now LLMs may not be a model for how we do it but they
               | are certainly going to bring back structuralist and
               | "wordcel" positions because they do seem to show,
               | somehow, that "language is all you need" to accomplish
               | whatever it is LLMs accomplish.
               | 
               | People will _try_ to bring back these obviously false
               | models of cognition, but, so far, the dismal performance
               | of LLMs on e.g. SpatialBench [1], and, almost certainly
               | ARC-AGI-3, or e.g. the kind of data and effort required
               | to get something like V-JEPA-2 [2], will be strong
               | counter-examples to this. And, yeah, obviously animal
               | cognition, esp. smart animals like birds, or the crazy
               | stuff we see in chimp and gorilla ethology (border
               | patrols, genocides, humor, theory of mind, bla bla bla).
               | 
               | [1] https://spicylemonade.github.io/spatialbench/
               | 
               | [2] https://arxiv.org/abs/2506.09985
        
         | uoaei wrote:
         | Language constrains your perception of reality to only the set
         | of concepts conceivable within that language.
         | 
         | Agents who only speak Rust have no conception of what runtime
         | errors are, for instance. Fascists won't understand concepts
         | like "universal human rights" as in their worldview there is
         | nothing universal about humanity as a whole.
        
           | PaulHoule wrote:
           | I'd argue that people can put words together to make new
           | meanings or coin new words when they have to. The real magic
           | of language is not "we have words for everything" but we have
           | grammar.
        
           | D-Machine wrote:
           | This is IMO largely false, and empirically things like Sapir-
           | Worf and _strong_ linguistic relativism, or that language ==
           | thought are widely considered disproven [1-3].
           | 
           | This is also sort of a wordcel take, in that it neglects that
           | there are plenty of mental structures that are not solely
           | linguistic. I.e. visuo-spatial models, auditory models,
           | kinaesthetic, proprioceptive, emotional, gustatory, or even
           | maybe intuitive models, and symbolic models (which have both
           | linguistic and visuo-spatial aspects). Yes, your models
           | constrain your perception of reality, but it is not clear how
           | important language really is to many of those models (and
           | there is strong evidence it may not matter at all to a lot of
           | cognition [3]).
           | 
           | [1] https://en.wikipedia.org/wiki/Linguistic_relativity
           | 
           | [2] https://plato.stanford.edu/archives/sum2015/entries/relat
           | ivi...
           | 
           | [3] https://pmc.ncbi.nlm.nih.gov/articles/PMC4874898/
        
             | paganel wrote:
             | Disproven by whom and under which context?
             | 
             | > evidence from neuroimaging and neurological patients
             | 
             | Has "neuroimaging" successfully modelled those "universal
             | human rights" the OP was mentioning? If yes, how did it
             | look?
             | 
             | More generally, positing that all languages are, in the
             | end, interchangeable (because that's what the opponents of
             | something similar to Sapir-Worf are saying) is very
             | reactionary and limited in itself, and its telling them me
             | calling those anti-Sapir-Worf people "reactionaries" will
             | for sure tickle in them something that wouldn't have
             | happened had I used a different "neuoroimaged" concept
             | which, supposedly, should have meant the same thing for
             | them (but it doesn't).
        
               | D-Machine wrote:
               | > Disproven by whom and under which context?
               | 
               | See any of my links, but especially the third. Animal
               | cognition and human neuroscience studies strongly
               | disprove the importance of language to cognition.
               | Conflating language and thought is so obviously false in
               | 2026 it is extraordinary that people still think like
               | this.
               | 
               | I was ignoring the comment about fascists because it is
               | simplistic and low-quality, and will similarly not be
               | responding to whatever you (incorrectly) think I was
               | claiming about universal human rights. I only wanted to
               | correct the extremely false (or at least hugely
               | overstated) assumptions about language and perception of
               | reality.
        
           | PurpleRamen wrote:
           | > Language constrains your perception of reality to only the
           | set of concepts conceivable within that language.
           | 
           | It's the opposite. People make up new concepts all the time
           | for which they have no words, to then give it a name.
           | Language is composable, words and names are just a mean to
           | improve communication, make it faster, more efficient.
           | 
           | > Agents who only speak Rust have no conception of what
           | runtime errors are, for instance.
           | 
           | Agents don't really learn. They have a fixed set of data and
           | everything new has to be pressed into the prompt. This is
           | unrelated to language.
        
         | yorwba wrote:
         | All LLM behavior is mediated through language by construction.
         | That doesn't mean the same applies to humans.
        
         | mitthrowaway2 wrote:
         | My interpretation is that it's the other way around. The
         | language model trainer's job is to find the network weights
         | that make the model best at compressing the data in the
         | training set. So what this means is that, say, professional
         | work-speak text samples and hacker l33t-speak text samples are
         | different enough that they end up being predicted by different
         | sparse sub-networks; it was apparently too hard to find a
         | smaller solution in which the same sub-network weights predict
         | both outputs.
        
       | D-Machine wrote:
       | The personality thing seems kind of tautological / uninteresting,
       | as I have pointed out before:
       | https://news.ycombinator.com/item?id=46905692.
       | 
       | Psychological instruments and concepts (like MBTI) are
       | constructed from the semantics of everyday language. Personality
       | models (being based on self-report, and not actual behaviour) are
       | not models of _actual_ personality, but the _correlation
       | patterns_ in the _language used_ to discuss things semantically
       | related to  "personality". It would be thus extremely surprising
       | if LLM-output patterns (trained on people's discussions and
       | thinking about personality) would not also result in learning
       | similar correlational patterns (and thus similar patterns of
       | responses when prompted with questions from personality
       | inventories).
       | 
       | The real and more interesting part of the paper is the use of
       | statistical techniques to isolate sub-networks which can then be
       | used to emit outputs more consistent with some desired
       | personality configuration. There is no obvious reason to me that
       | this couldn't be extended to other types of concepts, and it kind
       | reads to me like a way of doing a very cheap, training-free sort
       | of "fine-tuning".
        
         | devmor wrote:
         | Thank you, I came here to say so much in less eloquent terms.
         | 
         | It's not surprising to find clustered sentiment from a slice of
         | statistically correlated language. I wouldn't call this a
         | "personality" any more than I would say the front grill of a
         | car has a "face".
         | 
         | Deterministically isolating these clusters however, could prove
         | to be an incredibly useful technique for both using and
         | evaluating language models.
        
           | D-Machine wrote:
           | It's not even really the researchers' fault, academic
           | psychological personality research is in general
           | philosophically very weak / poor, in that they also almost
           | always conflate "models of / talking about personality" with
           | actual personality, and rarely actually check if things like
           | the MBTI or Five-Factor Model actually correlate meaningfully
           | with real behaviours.
           | 
           | Those that do find correlations between self-reported
           | personality and actual behaviours tend to find those to be in
           | a range of something like 0.0 to 0.3 or so, maybe 0.4 if you
           | are really lucky. Which means "personality" measured this way
           | is explaining something like 16% of the variance in
           | behaviour, at max.
        
             | devmor wrote:
             | I don't think this is even limited to this part of academia
             | - or academia at all, but I do think it's a bit
             | irresponsible of them to assume prior rigor in those
             | personality tests.
             | 
             | On top of that, a confounding issue is that human nature is
             | to anthropomorphize things. What is more likely to be
             | anthropomorphized than a construct of written language -
             | the now primary method of knowledge transfer between
             | humans? I can't help but feel that this wishful bias
             | contributes to missing the due diligence of choosing an
             | appropriate metric with which to measure.
        
               | D-Machine wrote:
               | Yup, I agree it is a general problem, and related to a
               | tendency to over-anthropomorphize. At least in this case
               | there was still something pretty good in the paper
               | anyway.
        
         | Nevermark wrote:
         | Agreed.
         | 
         | Everything in a model is a correlation of behavior with context
         | and context with behavior.
         | 
         | "Mind set" is a factor across the continuum of scales.
         | 
         | Are we solving a math problem or deciding on entertainment? We
         | become entirely "different brains" in those different contexts,
         | as we configure our behavior and reasoning patterns
         | accordingly.
         | 
         | The study is still interesting. The representation, clustering,
         | and bifurcations of roles may simply be one end of a continuum,
         | but they are still meaningful things to specifically
         | investigate.
        
         | observationist wrote:
         | Some sort of software like ComfyUI with variable application of
         | model specific personality traits would be great - increase
         | conscientiousness, decrease neuroticism, increase openness,
         | etc. Make it agentic; have it do intermittent updates based on
         | a record of experiences, and include all 27 emotional
         | categories, with an autonomous update process so it adapts to
         | interactions in real time:
         | https://www.pnas.org/doi/10.1073/pnas.1702247114
         | 
         | Could be very TARS like, lol.
         | 
         | It'd also be interesting to do a similar rolling record of
         | episodic memory, so your agent has a more human like memory of
         | interactions with you.
         | 
         | Another thing to consider about LLMs is that the nature of the
         | training and the core capability of transformers is to mimic
         | the function of the processes by which the training data was
         | produced; by training on human output, these LLMs are in many
         | cases implicitly modeling the neural processes in human brains
         | which resulted in the data. Lots of hacks, shortcuts, low
         | resolution "good enough" approximations, but in some cases,
         | it's uncovering precisely the same functions that we use in
         | processing and producing information.
        
           | D-Machine wrote:
           | > Another thing to consider about LLMs is that the nature of
           | the training and the core capability of transformers is to
           | mimic the function of the processes by which the training
           | data was produced; by training on human output, these LLMs
           | are in many cases implicitly modeling the neural processes in
           | human brains which resulted in the data. Lots of hacks,
           | shortcuts, low resolution "good enough" approximations, but
           | in some cases, it's uncovering precisely the same functions
           | that we use in processing and producing information.
           | 
           | I would argue this is deeply false, my classic go-to examples
           | being that neural networks have almost no real relations to
           | any aspects of actual brains [1] and that modeling even a
           | _single_ cortical neuron requires an entire, fairly deep
           | neural network [2]. Neural nets really have nothing to do
           | with brains, although brains may have loosely inspired the
           | earliest MLPs. Really NNs are just very powerful and
           | sophisticated curve (manifold) fitters.
           | 
           | > Could be very TARS like, lol.
           | 
           | I just rewatched Interstellar recently and this is such a
           | lovely thought in response to the paper!
           | 
           | [1] https://en.wikipedia.org/wiki/Biological_neuron_model
           | 
           | [2] https://www.sciencedirect.com/science/article/pii/S089662
           | 732...
        
             | observationist wrote:
             | >> I would argue this is deeply false
             | 
             | I am making the case that this is distinctly and
             | specifically true, for these types of models. They're
             | eliciting many of the underlying functions and processes
             | that brought about the data; transformers are able to model
             | the higher degrees of abstraction that previous neural
             | architectures could not. This was one of the major features
             | of transformers that make them so powerful.
             | 
             | It's comparable to the idea that if you trained a model to
             | output human sounding speech, many of the functions that
             | shape the voice will correspond to the physical attributes
             | that affect the sound of actual human voices. Volume of the
             | mouth, shape of the lips, position of teeth, what the
             | tongue does, etc - some of those things will be captured,
             | others will be mashed into "good enough" , and others will
             | be captured as an optimization possible in silicon but not
             | for flesh and blood. It's not a one to one correspondence,
             | but capturing process semantics and abstractions is why we
             | have ChatGPT with transformers and not CNNs (although RNNs
             | could have pulled it off back in the 90s, see: RWKV)
             | 
             | Anyway - the training methods, the paradigm of next token
             | generation (in contrast to things like diffusion) and other
             | aspects of LLMs restrict them to a subset of human
             | capabilities, but it's reasonable to make the claim that
             | many of the same functions that operate in Werncke's area
             | and Broca's area in the human brain are resident in
             | transformers. Many of the same associations between
             | language and emotion and those abstract correlations -
             | unspecified, implicit context that exists in the training
             | data, but only as a deep subtext, sometimes even
             | distributed across many texts, like cultural trends and so
             | forth - are modeled by LLMs, not as an explicit feature of
             | the data, but an implicit feature or function of the
             | processes which produced the data.
             | 
             | Plus, there seems to be some support for the idea that for
             | intelligent systems, modeling the world will result in
             | comparable structures, networks, and features for similar
             | concepts and knowledge - because you're modeling
             | consistent, persistent things using modalities that are
             | shared, or overlap, the way in which things are modeled
             | converges on "universal" forms, simply due to constraints
             | of utility and efficiency.
             | 
             | https://arxiv.org/abs/2405.07987
        
       | est wrote:
       | is this somehow related ?
       | 
       | https://www.anthropic.com/research/persona-selection-model
        
       | tl2do wrote:
       | The word "personality" smuggles in biological assumptions. Asking
       | "does this model have personality?" feels unproductive because
       | the term implies something it can't be.
       | 
       | More useful framing: how do these subnetworks produce outputs
       | that _observers evaluate_ as personality-consistent? Personality
       | isn 't an internal property - it's a judgment made by people
       | watching behavior.
        
         | D-Machine wrote:
         | > Personality isn't an internal property - it's a judgment made
         | by people watching behavior.
         | 
         | Partly, yes, but personality _is_ also an internal property, or
         | it is coherent and correct enough to generally say that it has
         | internal aspects. I.e. a person 's personality is the set of
         | (relatively) stable and difficult-to-change patterns that
         | manifest in their behaviour in broad contexts, and these
         | patterns are almost certainly encoded internally in the brain
         | in some form. It is not much different than saying a person's
         | intelligence / IQ is partly internal.
         | 
         | Otherwise, I do agree with your more careful framing, and I
         | wish people thought and spoke more carefully about these
         | things, and doubly so for LLMs.
        
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