From 0% to 36% on Day 1 of ARC-AGI-3
37 points
2 hours ago
| 3 comments
| symbolica.ai
| HN
lairv
2 hours ago
[-]
Note that this uses a harness so it doesn't qualify for the official ARC-AGI-3 leaderboard

According to the authors the harness isn't ARC-AGI specific though https://x.com/agenticasdk/status/2037335806264971461

reply
krackers
34 minutes ago
[-]
> this uses a harness

This seems like an arbitrary restriction. Tool-use requires a harness, and their whitepaper never defines exactly what counts as valid.

reply
osti
17 minutes ago
[-]
Doesn't the chat version of chatgpt or gemini also have interleaved tool calls, so do those also count as with harnesses?
reply
falcor84
1 hour ago
[-]
I for one think that harness development is perhaps the most interesting part at the moment and would love to have an alternative leaderboard with harnesses.
reply
steve_adams_86
13 minutes ago
[-]
I'm so into harness development right now. Once it clicked that harnesses can bring more safety and determinism to LLMs, I started to wonder where I'd need that and why (vs MCP or just throwing Claude Code at everything), and my brain gears have been turning endlessly since then. I'd love to see more of what people do with them. My use cases are admittedly lame and boring, but it's such a fun paradigm to think and develop around.
reply
sanxiyn
1 hour ago
[-]
There is. Official leaderboard is without harness, and community leaderboard is with harness. Read ARC-AGI-3 Technical Paper for details.
reply
falcor84
1 hour ago
[-]
I went through the technical paper again, and while they explain why they decided against the harness, I disagree with them - my take is that if harnesses are overfitting, then they should be penalized on the hidden test set.

Anyway, searching both in ARC-AGI's paper and website and directly on kaggle, I failed to find a with-harness leaderboard; can you please give the link?

reply
sanxiyn
1 hour ago
[-]
reply
modeless
16 minutes ago
[-]
On the public set of 25 problems. These are intended for development and testing, not evaluation. There are 110 private problems for actual evaluation purposes, and the ARC-AGI-3 paper says "the public set is materially easier than the private set".
reply
SchemaLoad
15 minutes ago
[-]
Benchmarks on public tests are too easy to game. The model owners can just incorporate the answers in to the dataset. Only the private problems actually matter.
reply
sanxiyn
11 minutes ago
[-]
In this case the code is public and you can see they are not cheating in that sense.
reply
SchemaLoad
7 minutes ago
[-]
Once the model has seen the questions and answers in the training stage, the questions are worthless. Only a test using previously unseen questions has merit.
reply
lambda
2 minutes ago
[-]
They aren't training new models for this. This is an agent harness for Opus 4.6.
reply
esafak
1 hour ago
[-]
Anybody used this Agentica of theirs?
reply