Suproteem Sarkar ✓

@SuproteemSarkar

Assistant Professor @UChicago

1 015Followers

274Following

82Posts total

98KViews on collected posts

โพสต์ล่าสุด

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 →

เทียบกับบัญชีขนาดเดียวกัน

6 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง under 10K ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.

ยอดดูมัธยฐาน7 041บัญชีนี้4 175ค่ามัธยฐานของ under 10K

การเข้าถึง, %693.69%บัญชีนี้250.82%ค่ามัธยฐานของ under 10K

การมีส่วนร่วม, %0.60%บัญชีนี้1.41%ค่ามัธยฐานของ under 10K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ under 10K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	7 041	4 175	1.69×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	6.9× audience	2.5× audience	2.77×
อัตราการมีส่วนร่วม	0.60%	1.41%	0.43×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

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.

โพสต์ล่าสุด

เทียบกับบัญชีขนาดเดียวกัน

Growth & engagement

Views per post

Engagement rate per post

What the audience does

บัญชีที่คล้ายกัน