Haven Feng ✓

@HavenFeng

Postdoc @berkeley_ai, building Impossible. Prev. @MPI_IS @AdobeResearch @uni_tue Interested in recreating the physical world and the intelligence to do so.

5 228Followers

1 119Following

259Posts total

1.1MViews on collected posts

Postingan terbaru

Haven Feng ✓@HavenFeng16 Jul

@HavenFeng thinking like a physicist is all you need? 6.5K views · 46 likes · 0 reposts · 2 replies Open on X →

Haven Feng ✓@HavenFeng16 Jul

@guanningzeng @Jiani_Wang_ @wenjie_ma @shaofeng_y27736 @arcprize 16.6K views · 98 likes · 0 reposts · 3 replies Open on X →

Haven Feng ✓@HavenFeng16 Jul

[schema]'s saturation of the ARC-AGI-3 public set is only a starting point. There is much more to explore! Full blog: https://t.co/A13KTXczUX Agent traces: https://t.co/Gc6hP4OitW Amazing team effort with @guanningzeng, @Jiani_Wang_, @wenjie_ma, @shaofeng_y27736, https://t.co/b

25.9K views · 223 likes · 14 reposts · 3 replies Open on X →

Haven Feng ✓@HavenFeng16 Jul

[schema] handles the state and mechanism in one editable program, a symbolic world model. It designs experiments to verify hypotheses, backtests the program against history, and plans inside its world at zero action cost. 24.7K views · 143 likes · 6 reposts · 2 replies Open on X →

Haven Feng ✓@HavenFeng16 Jul

ARC-AGI-3 gives an agent a 64×64 grid plus legal actions, no rules, stated goal, or reward. The agent must discover both what the world is and how it works like a physicist: 1. State grounding -> identify objects, relations, and goals. 2. Mechanism discovery -> infer how these h

31.3K views · 203 likes · 4 reposts · 7 replies Open on X →

Haven Feng ✓@HavenFeng16 Jul

Today, we’re introducing [schema]: a harness reaching 99% RHAE with Opus 4.8 + Fable 5 and 95.35% with GPT-5.6 Sol on ARC-AGI-3 Public set. [schema] makes an LLM think like a physicist. 🧵 https://t.co/U0C0JFj62e

0:47

950K views · 2.5K likes · 297 reposts · 125 replies Open on X →

Dibandingkan akun berukuran sama

6 postingan dari 90 hari terakhir, dibandingkan dengan rentang under 10K pengikut. tampil luas, tetapi sedikit penonton yang merespons.

Median tayangan25 306akun ini4 175median untuk under 10K

Jangkauan, %484.04%akun ini250.82%median untuk under 10K

Interaksi, %0.66%akun ini1.41%median untuk under 10K

Metrik	Akun ini	Median untuk under 10K	Rasio
Median tayangan per postingan	25 306	4 175	6.06×
Jangkauan (tayangan ÷ pengikut)	4.8× audience	2.5× audience	1.93×
Tingkat interaksi	0.66%	1.41%	0.47×

Akun lain pada rentang ini → Bandingkan dengan akun lain → Bagaimana tolok ukur ini disusun →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

950K16 Jul

31.3K

24.7K

25.9K

16.6K

6.5K

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.32%16 Jul

0.69%

0.62%

0.94%

0.61%

0.74%

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.41%.

What the audience does

Likes51.5%3 207 in total

Reposts5.2%321 in total

Replies2.3%142 in total

Quotes2.3%143 in total

Bookmarks38.7%2 409 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Postingan terbaru

Dibandingkan akun berukuran sama

Growth & engagement

Views per post

Engagement rate per post

What the audience does

Akun serupa