Yibo (Leo) Wang

CS, UIUC @UofIllinois | ex intern, NetEase & Tencent

[Honing Lab @HoningLab]

New arena unlocked 🎮

We’ve added REA, an Isaac-inspired room-combat engine, to HoningLab.

Next up: letting our decision model step into the arena and see how it handles the fight. 🤖⚔️

More fun stuff on GitHub 👇
https://t.co/dQ3I8tngi9

[Yibo (Leo) Wang @Leow_sss730]

Inspired by weight-space work, we tried the same idea on the decision problem. Follow @HoningLab and our GitHub repository to find more fun stuff!

[Haoze He @HaozeHe_Hector]

We edited 0.0002% of NanoJev’s weights, and the edited model beat the original 65–34 (1 draw) in 100 head-to-head Tank War games. 🎯

The original took only about 1 in 3 clean shots. Using Weight-Space Programming by @rikiyatakehi et al. (https://t.co/oQW1HI5rU9), we read the fire-vs-hold direction out of its activations and added it to the decision head: 1,024 weights, no training. Now it takes every clean shot and fires about twice as often.

It isn’t a better shot, though. It just stopped hesitating.

🛠️ Weight editing is now a trainer in Honing. An edit goes through the same gate as SFT and RL, and only ships if it beats the current model.

Report: https://t.co/xpLcLMauje

Weight-edit trainer: https://t.co/hoXdxumA1s

GitHub: https://t.co/oAPAOkCpcy
Follow @HoningLab for more Honing updates :)

[Honing Lab @HoningLab]

100+ GitHub stars! 🌟 Sadly, our agents can’t train on those. Back to the GPUs. 🫠

This week: SGLang serving + an OpenHands/OfficeQA integration landed in Honing. The toolkit is growing beyond games.

Thanks for the early support! 🫶

[Yibo (Leo) Wang @Leow_sss730]

Happy to be part of this project. RA2 has been with me since childhood, so seeing it become a testbed for decision models feels personal. 🥳

What excites me most going forward: how fast, tactical responses and long-term strategic planning can work together in the same game.

[Haoze He @HaozeHe_Hector]

Try it on https://t.co/Xmjb9TddPw and to play against one of our best models!

We gave open-source decision models two games. It did not go well. 🫠

🎮 Red Alert 2: the base model sold its own base. Then lost.
💥 Tank War: v1 spun in circles. v2 found the fire button… and shot itself.

So we let them keep learning: play → train → upgrade the harness → repeat. A few rounds later: model can evolve without human intervention

Then we put different models in one arena and let them fight it out. So far, no human has beaten the trained models. 😅

The lesson: a decision model isn't finished when it's released. Real environments keep throwing new situations at it, and a frozen model can't adapt. It needs continuous learning!

It's all open source: how we train these models to play, end to end. Next, we're turning it into training infra for any decision model.

⭐ Star it, fork it, or bring your own model to the arena:
GitHub: https://t.co/oAPAOkBRn0
RA2: https://t.co/xMv6VNaE11
Tank War: https://t.co/xttz2fjeWe

I also appreciate all the suggestions and feedback from: @b_vasilescu , Greg Ganger, @p0nk , @lateinteraction , @matei_zaharia , and @heathercmiller

And thanks to all the Contributors to the demo and the github repo!: @Jayzou3773, @brocoliman38951,
@ShangyinT , @Xuan04263449 , chenyang yang, tianyu chen , @AlexZhang152005, @Nickzz12138,@JasonWuzh, @Leow_sss730, @ChenMoneyQ , xingyuan ding, @JunchengLi , @LakshyAAAgrawal , @ao_qu18465

[Haoze He @HaozeHe_Hector]

Try it on https://t.co/Xmjb9TddPw and to play against one of our best models!

We gave open-source decision models two games. It did not go well. 🫠

🎮 Red Alert 2: the base model sold its own base. Then lost.
💥 Tank War: v1 spun in circles. v2 found the fire button… and shot itself.

So we let them keep learning: play → train → upgrade the harness → repeat. A few rounds later: model can evolve without human intervention

Then we put different models in one arena and let them fight it out. So far, no human has beaten the trained models. 😅

The lesson: a decision model isn't finished when it's released. Real environments keep throwing new situations at it, and a frozen model can't adapt. It needs continuous learning!

It's all open source: how we train these models to play, end to end. Next, we're turning it into training infra for any decision model.

⭐ Star it, fork it, or bring your own model to the arena:
GitHub: https://t.co/oAPAOkBRn0
RA2: https://t.co/xMv6VNaE11
Tank War: https://t.co/xttz2fjeWe

I also appreciate all the suggestions and feedback from: @b_vasilescu , Greg Ganger, @p0nk , @lateinteraction , @matei_zaharia , and @heathercmiller

And thanks to all the Contributors to the demo and the github repo!: @Jayzou3773, @brocoliman38951,
@ShangyinT , @Xuan04263449 , chenyang yang, tianyu chen , @AlexZhang152005, @Nickzz12138,@JasonWuzh, @Leow_sss730, @ChenMoneyQ , xingyuan ding, @JunchengLi , @LakshyAAAgrawal , @ao_qu18465

[Yibo (Leo) Wang @Leow_sss730]

@Jayzou3773 I would call it Kaiology/Jayology🤣