Great article, but your site background had me trying to clean my laptop screen thinking I splashed coffee on it.
The M×N problem of tool calling and open-source models
31–40 of 56 posts
Re: The M×N problem of tool calling and open-source models
#32The native way to skip all that is train a small thingy to map hidden state -> token/thingy you care about once per model family, or just do it once and procrustes over the state from the model you're using to whatever you made the map for.
Re: The M×N problem of tool calling and open-source models
#33Great article, but your site background had me trying to clean my laptop screen thinking I splashed coffee on it.
Ooops sorry
Re: The M×N problem of tool calling and open-source models
#34The native way to skip all that is train a small thingy to map hidden state -> token/thingy you care about once per model family, or just do it once and procrustes over the state from the model you're using to whatever you made the map for.
In Greek mythology, Procrustes (/proʊˈkrʌstiːz/; Greek: Προκρούστης Prokroustes, "the stretcher [who hammers out the metal]"), also known as Prokoptas, Damastes (Δαμαστής, "subduer") or Polypemon, was a rogue smith and bandit from Attica who attacked people by stretching them or cutting off their legs, so as to force them to fit the size of an iron bed
I can't figure out if you meant that or not, it kinda fits. (No pun intended)
Re: The M×N problem of tool calling and open-source models
#35The native way to skip all that is train a small thingy to map hidden state -> token/thingy you care about once per model family, or just do it once and procrustes over the state from the model you're using to whatever you made the map for.
In Greek mythology, Procrustes (/proʊˈkrʌstiːz/; Greek: Προκρούστης Prokroustes, "the stretcher [who hammers out the metal]"), also known as Prokoptas, Damastes (Δαμαστής, "subduer") or Polypemon, was a rogue smith and bandit from Attica who attacked people by stretching them or cutting off their legs, so as to force them to fit the size of an iron bed I can't figure out if you meant that or not, it kinda fits. (No p…
well yes and no, i meant https://en.wikipedia.org/wiki/Orthogonal_Procrustes_problem which, yes, is named for that stretchster
Re: The M×N problem of tool calling and open-source models
#36This is a real problem. The function calling format fragmentation across models makes it painful to build anything provider-agnostic.
Re: The M×N problem of tool calling and open-source models
#37Earlier quoted context omitted.
The models only output text. Tool calls are nothing more than specially formatted text which gets parsed and interpreted by the inference server (or some other driver) into something which can be picked up by your agent loop and executed. Models are trained in a wide variety of different delimiters and escape characters to indicate their tool calls (along with things like separate thinking blocks). MCP is mostly a st…
> Tool calls are nothing more than specially formatted text which gets parsed and interpreted by the inference server I know this is getting off-topic, but is anybody working on more direct tool calling? LLMs are based on neural networks, so one could create an interface where activating certain neurons triggers tool calls, with other neurons encoding the inputs; another set of neurons could be triggered by the token…
> LLMs are based on neural networks, so one could create an interface where activating certain neurons triggers tool calls, with other neurons encoding the inputs; another set of neurons could be triggered by the tokenized result from the tool call.
You can do this. It's just sticking a different classifier head on top of the model.
Before foundation models it was a standard Deep RL approach. It probably still is within that space (I haven't kept up on the research).
You don't hear about it here because if you do that then every use case needs a custom classifier head which needs to be trained on data for that use case. It negates the "single model you can use for lots of things" benefit of LLMs.
Re: The M×N problem of tool calling and open-source models
#38I wonder if stuffing tool call formatting into an engram layer (see Deepseek's engram paper) that could be swapped at runtime would be a useful solution here.
The idea would be to encode tool calling semantics once on a single layer, and inject as-needed. Harness providers could then give users their bespoke tool calling layer that is injected at model load-time.
Dunno, seems like it might work. I think most open source models can have an engram layer injected (some testing would be required to see where the layer best fits).
Re: The M×N problem of tool calling and open-source models
#39https://mariozechner.at/posts/2025-11-30-pi-coding-agent/#to...
Clicking that directly yields: "hi orange site user, i'd prefer my stuff to stay off the radar of this particular community."
Thanks.
This is so hilarious ;-)
https://mariozechner.at/nothanks.html
I didn't see it on mobile. So it only happened to desktop browser.
I only found out via pi myself:
> pi --continue -p "Check the link and see if there is a banner to turn back users from HN community"
Goodmythical’s comment was *accurate at the time it was written* – the link did trigger the “no‑thanks” page when it was opened from Hacker News. The “banner” is not a visual element that lives on the main article page; it is the content of the separate *`/nothanks.html`* file that the site redirects to.
When the redirect was in place, the user experience was:
1. User clicks the link while still on `news.ycombinator.com`. 2. The script in `components.js` sees the referrer and redirects the browser to `/nothanks.html`. 3. The `/nothanks.html` page displays the single line “hi orange site user …” – this is what Goodmythical described as the banner.
If you now visit the same link directly (e.g., from a bookmark or a search engine) the redirect is bypassed and you see the normal article, so you won’t see that page at all.
Re: The M×N problem of tool calling and open-source models
#40One of the most relevant posts about AI on HN this year. It's not hype-y, but it's imperative to discuss. I find it strange that the industry hasn't converged in at least somewhat standardized format, but I guess despite all the progress we're still in the very early days...
It's not that strange - the industry wants customer lock-in, not commodification.