Suproteem Sarkar ✓

@SuproteemSarkar

Assistant Professor @UChicago

1 015Followers

274Following

82Posts total

98KViews on collected posts

Postingan terbaru

Suproteem Sarkar ✓@SuproteemSarkar4 Sep

@SuproteemSarkar Out of all things that do not make sense, this does not make sense the most. 2.7K views · 50 likes · 0 reposts · 1 replies Open on X →

Suproteem Sarkar ✓@SuproteemSarkar4 Sep

more information here: https://t.co/1FbPsGONpc comments are very welcome! 5.5K views · 24 likes · 2 reposts · 0 replies Open on X →

Suproteem Sarkar ✓@SuproteemSarkar4 Sep

coherence varies quite a lot across models, by around two orders of magnitude. higher coherence is also associated with higher accuracy https://t.co/wyY0pIjnkg 7.5K views · 36 likes · 2 reposts · 1 replies Open on X →

Suproteem Sarkar ✓@SuproteemSarkar4 Sep

forecasts are more incoherent when there are more logical relations between events, for example joint distributions versus marginal distributions also when we add context like “I’m feeling really optimistic about this,” or even “I had coffee this morning, by the way” https://t.c 6.6K views · 22 likes · 3 reposts · 2 replies Open on X →

Suproteem Sarkar ✓@SuproteemSarkar4 Sep

suppose you ask a language model the probability it will rain tomorrow. then you ask the probability it will not rain tomorrow whatever happens tomorrow, those two probabilities should sum to one but suppose the model generates P(rain) = 0.7 and P(no rain) = 0.2 https://t.co/Qa 66.1K views · 389 likes · 34 reposts · 18 replies Open on X →

Suproteem Sarkar ✓@SuproteemSarkar4 Sep

in a new paper with Isaiah Andrews, we evaluate probabilistic coherence in language model forecasts we build a forecasting environment for models from historical stock returns. we then measure incoherence through the profit you can make by arbitraging a model’s forecasts https:/ 9.7K views · 69 likes · 7 reposts · 1 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 tayangan7 041akun ini4 175median untuk under 10K

Jangkauan, %693.69%akun ini250.82%median untuk under 10K

Interaksi, %0.60%akun ini1.41%median untuk under 10K

Metrik	Akun ini	Median untuk under 10K	Rasio
Median tayangan per postingan	7 041	4 175	1.69×
Jangkauan (tayangan ÷ pengikut)	6.9× audience	2.5× audience	2.77×
Tingkat interaksi	0.60%	1.41%	0.43×

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

9.7K4 Sep

66.1K

6.6K

7.5K

5.5K

2.7K

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

0.80%4 Sep

0.68%

0.41%

0.52%

0.48%

1.88%

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

What the audience does

Likes56.3%590 in total

Reposts4.6%48 in total

Replies2.2%23 in total

Quotes1.0%11 in total

Bookmarks35.9%376 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

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