alex zhang ✓
@a1zhang · USA · joined 24 Dec 2015
phd student @mit_csail @nlp_mit, previously undergrad @princeton 🫵🏻 go participate in the @GPU_MODE kernel competitions!
38 007Followers
1 021Following
1 230Posts total
370KViews on collected posts
Последние посты
Ищем новые посты…
actually coolest thing I've read in a long time (and + points for being well written and to the point!)
I guess a natural question in the language domain is whether a natural clustering of "tasks" is obvious enough to a human s.t. doing search over new archs has some clear goal
33.5K views · 300 likes
· 8 reposts · 2 replies
Open on X →
A bit different than my usual research content but a friend who has poured a lot into her indie game has finally released it! They don't have a huge Twitter following but I wanted to shout them out!
Go check it out, it's a really engaging game :)
8.9K views · 76 likes
· 3 reposts · 4 replies
Open on X →
Ventreville: A Cure for Sorrow is AVAILABLE NOW!
We’ve come a long way from friends playing an original Dungeons & Dragons campaign to an indie studio crafting our mystery into a video game.
Check out Ch. 1 on Steam 🕵️🥐🧪
https://t.co/dYJ54juugU https://t.co/6L7RoHL308
9.5K views · 20 likes
· 2 reposts · 0 replies
Open on X →
alphaXiv had this up day 1, they now support blogs!
https://t.co/USLkKLrsx5
10.5K views · 113 likes
· 7 reposts · 3 replies
Open on X →
“Speculative Programmatic Tool Calling”
Code agents waste time waiting for the LLM to finish generating code before tool calls can start.
So this paper speculatively executes predictable tool calls from partial generations, while a shadow REPL tracks dependencies safely.
This
16.4K views · 84 likes
· 8 reposts · 3 replies
Open on X →
Speculative Programmatic Tool Calling (sPTC) Explained! 🔥
👉 https://t.co/ALWTSyO7q7 https://t.co/ru324hkFO4
17.6K views · 82 likes
· 11 reposts · 5 replies
Open on X →
The codebase is very simple, and you can easily build on top of it for your own plugins. We provide an example of patching the RLM, which will be included in the RLM codebase.
https://t.co/1UHINaT2M9
4.3K views · 57 likes
· 3 reposts · 1 replies
Open on X →
We talk a bit in the blog about what you can safely speculate on, and how. We run a "shadowed" REPL with its own namespace to resolve input dependencies when necessary.
These rules will likely evolve over time, but are as simple as possible for now. https://t.co/IAp1MOnqUJ
5.1K views · 33 likes
· 2 reposts · 1 replies
Open on X →
We want to speculate in two cases:
1. To overlap with the LLM streaming outputs, especially when thinking.
2. To overlap with actual REPL execution time, which can be expensive. This can be thought of as JIT compiling when you have stronger priors about tool calls. https://t.co/z
9.5K views · 94 likes
· 4 reposts · 1 replies
Open on X →
We run a small experiment over the RLM on information-dense tasks, and focus on the sub-LLM call as the tool of interest.
These runs are high variance, and over 5 runs we find 1-1.2x gains in speed on similar trajectories.
We also test over more deterministic examples in the ht
6.4K views · 47 likes
· 2 reposts · 1 replies
Open on X →
Introducing Speculative Programmatic Tool Calling (sPTC)!
A general class of technique for speculating on tool calls during code generation in a harness and queuing them early to overlap with token generation + REPL execution time.
Blog: https://t.co/0nzkLvTXNy https://t.co/SVH
236.1K views · 1.8K likes
· 204 reposts · 58 replies
Open on X →
На фоне аккаунтов своего размера
13 постов за последние 90 дней рядом с диапазоном 10K–100K подписчиков. показывается широко, но откликается мало кто.
Медианные просмотры9 525этот аккаунт924медиана для 10K–100K
Охват, %25.06%этот аккаунт3.62%медиана для 10K–100K
Вовлечённость, %0.88%этот аккаунт1.52%медиана для 10K–100K
| Показатель | Этот аккаунт | Медиана для 10K–100K | Отношение |
|---|---|---|---|
| Медианные просмотры на пост | 9 525 | 924 | 10.3× |
| Охват (просмотры ÷ подписчики) | 25.06% | 3.62% | 6.92× |
| Вовлечённость | 0.88% | 1.52% | 0.58× |
Другие в этом диапазоне → Сравнить с другим аккаунтом → Как считаются эти ориентиры →
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
236.1K24 Aug
6.4K
9.5K
5.1K
4.3K
2.3K
17.6K25 Aug
9.8K
16.4K
10.5K26 Aug
9.5K28 Aug
8.9K
33.5K3 Sep
Last 13 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.88%24 Aug
0.78%
1.05%
0.70%
1.40%
0.90%
0.57%25 Aug
0.85%
0.60%
1.17%26 Aug
0.25%28 Aug
0.94%
0.93%3 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes52.1%2 762 in total
Reposts4.9%262 in total
Replies1.6%86 in total
Quotes1.1%60 in total
Bookmarks40.2%2 132 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.
Похожие аккаунты
Health Nest ✓
@OurHealthNest
76K followers
· 11.9K posts
ƤƖҲƖЄ ✓
@Pixie1z
76K followers
· 872K posts
𝗚𝗘𝗡𝗘𝗥𝗔𝗧𝗜𝗢𝗡 𝗢𝗙 𝗦𝗖𝗔𝗥𝗦
@rocknrollscars
76K followers
· 11.8K posts
t°Jabar ✓
@tijabar
76K followers
· 107.4K posts
Chairwoman Lisa McClain ✓
@RepLisaMcClain
76K followers
· 6.5K posts
Total Sports Enterprises ✓
@TotalSportsEnt
76K followers
· 17.6K posts
Chanley Shá Painter
@ChanleySPainter
76K followers
· 13.7K posts
SHL.se ✓
@SHLse
76K followers
· 40.4K posts