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Rosanne Liu

@savvyRL · San Francisco, CA · joined 03 Mar 2013

Cofounded & running @ml_collective. Weekly talks at Deep Learning Classics & Trends (DLCT). Research at Google DeepMind. DEI/DIA Chair of ICLR & NeurIPS.

55 546Followers
1 070Following
4 944Posts total
243.9KViews on collected posts

Neueste Beiträge

@savvyRL The variable iteration depth is exactly the important distinction. For any fixed number of iterations, you can unroll the model into a deeper network with tied parameters. But a fixed unrolling has fixed computational depth, whereas a loop can use an input-dependent numb 1.3K views · 10 likes · 1 reposts · 3 replies Open on X →
We talked about this extensively in "The Topological Trouble With Transformers" (arxiv: 2604.17121) and in "Recirculation" (arxiv: 2608.17981) 3.2K views · 26 likes · 2 reposts · 1 replies Open on X →
However many loops you do, the transformer is still inherently feedforward, the only "recurrence" added here is "depth recurrence", which is the same as making the model deeper (with tied parameters). The only real "recurrence" is if you carry things *forward in time*. 3.4K views · 32 likes · 1 reposts · 1 replies Open on X →
Stop blowing up Looped Transformers — it's not magical, it doesn't add recurrence to the (still and always) feedforward network, it was done years ago (Dehghani et al., 2019). All it does is making your model deeper, the same as if you added more layers to begin with. 46.9K views · 346 likes · 15 reposts · 13 replies Open on X →
100%! The title we secretly want to publish it under is "Recirculation. OR: CoT is a cop out." 4K views · 20 likes · 0 reposts · 4 replies Open on X →
@mc_mozer Interesting distinction from chain-of-thought. CoT is the default for reasoning gains, but state tracking feels more fundamental. If feedforward depth limits state updates, inference-time recurrence is a natural fix. 7.7K views · 4 likes · 1 reposts · 2 replies Open on X →
18 years into paper publishing and I still sheepishly search for our new paper title to see if it's gotten picked up in the gap between arxiv posted and twitter announced 7.2K views · 90 likes · 1 reposts · 2 replies Open on X →
On a two week vacation aka full time childcaring with no pay no appreciation and 24h on call where your coworker is kinda a jerk but super duper cute 8.9K views · 40 likes · 0 reposts · 6 replies Open on X →
@savvyRL @ml_collective @DeepIndaba I will forever be grateful for this noble effort. It is indeed a rare opportunity for the @ml_collective community 708 views · 6 likes · 0 reposts · 0 replies Open on X →
This year we have 25 amazing researchers to sponsor. For the first time we ask them to film a video about themselves. It's nothing like the usual well-polished, professional fundraiser video you'd stumble upon, but give it a watch: https://t.co/zkX35g93mI 7.6K views · 40 likes · 15 reposts · 1 replies Open on X →
We are raising $20k (which amounts to $800 per person), to cover their travel and lodging to Kigali, Rwanda in August, from either Nigeria or Ghana. Donate what you can here! https://t.co/ryCItIoxNs 14.7K views · 49 likes · 27 reposts · 0 replies Open on X →
The opportunity gap in AI is more striking than ever. We talk way too much about those receiving $100M or whatever for their jobs, but not enough those asking for <$1k to present their work. For 3rd year in a row, @ml_collective is raising funds to support @DeepIndaba attendees.
138.3K views · 262 likes · 118 reposts · 22 replies Open on X →

Im Vergleich zu Konten gleicher Größe

8 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.

Medianaufrufe5 574dieses Konto995Median für 10K–100K
Reichweite, %10.03%dieses Konto3.85%Median für 10K–100K
Interaktion, %0.85%dieses Konto1.52%Median für 10K–100K
KennzahlDieses KontoMedian für 10K–100KVerhältnis
Medianaufrufe pro Beitrag5 5749955.60×
Reichweite (Aufrufe ÷ Follower)10.03%3.85%2.61×
Interaktionsrate0.85%1.52%0.56×

Weitere Konten dieser Größe →   Mit einem anderen Konto vergleichen →   Wie diese Vergleichswerte entstehen →

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

138.3K10 Jul
14.7K
7.6K
708
8.9K27 Jul
7.2K19 Aug
7.7K20 Aug
4K
46.9K2 Sep
3.4K
3.2K
1.3K

Last 12 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.29%10 Jul
0.52%
0.73%
0.85%
0.52%27 Jul
1.29%19 Aug
0.09%20 Aug
0.61%
0.80%2 Sep
0.99%
0.91%
1.06%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes68.5%925 in total
Reposts13.4%181 in total
Replies4.1%55 in total
Bookmarks14.0%189 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.

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