Dani Balcells

Machine learning interpretability researcher

[Dani Balcells @danibalcells]

@readwise Very cool! Is there any way I can bring my Kindle purchases over, including existing highlights? I also often find myself buying on Kindle because of the Audible companions (though I can't tap to highlight!). Any plans to integrate audiobooks? Thanks!!

[Dani Balcells @danibalcells]

@exploding_grad @zfjoshying Thanks for the breakdown!

[Dani Balcells @danibalcells]

Super cool work by @LeonGuertler and the TextArena team! Very excited to have collaborated on this :)

[León @LeonGuertler]

For the past ~2 months we have been working on training reasoning models on TextArena games. The first paper (introducing what we think is a very promising new paradigm) will hopefully be up later this week / early next; and the second one, focusing on the "scaling laws" of self-play and some additional analysis, tentatively around the 18th of july.

However, to get more feedback on the structure and implementation, we want to open-source the code now.

UnstableBaselines is a very simple Async, Online, Multi-Turn, Multi-Agent RL library built on vLLM and Ray. The code is pretty readable and around 1.2k lines long (and includes a cool rendering interface that you can run via "unstable-terminal")

1/7

[Dani Balcells @danibalcells]

Minimum vibable product.

[Dani Balcells @danibalcells]

@homsiT @readwise It would be my honor and craving.

[León @LeonGuertler]

TextArena is live on arXiv! We present a benchmark of 57+ competitive text-based games to evaluate and train LLMs on agentic behavior — including negotiation, deception, theory of mind and many more. Real-time TrueSkill. Multiplayer support. Human-vs-models. Model-vs-model. Perfect environment for Multi-Agent, multi-turn reasoning and Planning! [1/N]

[Dani Balcells @danibalcells]

@plasticlabs @variantfund @WhiteStarCap @betaworks @honchodotdev empire theory of mind 🌌

[Dani Balcells @danibalcells]

It's always possible that they would do a lot better with 100x more inference-time compute. Still, this is a different regime from coding or math, where the motivation for expensive reasoning models is that other models simply do a bad job. Here, Claude 3.7 is cheaper AND better.

[Dani Balcells @danibalcells]

However, it involves reasoning about cues that reasoning models might not be as sensitive to after SFT and RL: choice of words, personal style, mood... We wonder if the post-training that makes them so good at math and coding also makes them worse at reading social cues.