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Jerry Liu ✓

@jerryjliu0 · joined 07 Sep 2011

Parsing the world's hardest PDFs @llama_index. cofounder/CEO Careers: https://t.co/EUnMNmbCtx Enterprise: https://t.co/Ht5jwxSrQB

84 315Followers
1 590Following
7 673Posts total
285.1KViews on collected posts

Latest posts

least reactionary take on X 5.2K views · 21 likes · 1 reposts · 2 replies Open on X →
Opus 5.5 is the best frontier model for parsing tables in PDFs. We ran it through ParseBench, and it scored 93.9%, a 7%+ increase over Opus 5, and beating Fable/Gemini/Astra. It's comparable to LlamaParse Agentic Plus in table quality, though it still struggles on charts, https
5.2K views · 82 likes · 9 reposts · 10 replies Open on X →
liteparse is the fastest pdf parser on the planet parses each page at just 2.8ms / page!! check it out: https://t.co/VfA6yJwzcZ https://t.co/vGsfeBJZuB
15.1K views · 146 likes · 8 reposts · 10 replies Open on X →
DocJev is the fastest way to classify and split complex document packets ⚡️. (and the default is fully free and OSS!) I made a sick teaser video below. TY Opus 5.5 🙏 check it out: https://t.co/fgSUUCWcwI https://t.co/7VbUMgCtyH
0:30
51.1K views · 564 likes · 44 reposts · 16 replies Open on X →
The fastest PDF-to-Markdown parser just got faster. ⚡️ With LiteParse v2.14.6, text-based PDFs parse about 25% faster. Across realistic documents, LiteParse processed pages at 2.8ms/page and 1.5× faster than the next-fastest local parser. LiteParse is open source and runs http
20.2K views · 50 likes · 1 reposts · 10 replies Open on X →
Introducing DocJev - a lightning-fast OSS library for document classification and splitting with jev ⚡️ Give a document alongside some natural language category rules. Jev will predict the document category (classify) or the boundaries between sub-documents (split). It is 6x ht
0:24
168.8K views · 1.1K likes · 98 reposts · 43 replies Open on X →
If you are looking to parse large volumes of PDFs (and other document formats) while maximizing accuracy and cost, we're offering $1k in credits if you signup to the Pro plan! We're guaranteeing high quality and low cost. If you run into issues on the Pro plan we're always http
19.4K views · 27 likes · 3 reposts · 2 replies Open on X →

Against accounts of the same size

7 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views19 423this account992median for 10K–100K
Reach, %23.04%this account3.89%median for 10K–100K
Engagement, %0.77%this account1.54%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post19 42399219.6×
Reach (views ÷ followers)23.04%3.89%5.92×
Engagement rate0.77%1.54%0.50×

Others in this range →   Compare with another account →   How these benchmarks are built →

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

19.4K26 Aug
168.8K20 Sep
20.2K22 Sep
51.1K
15.1K
5.2K
5.2K23 Sep

Last 7 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.17%26 Aug
0.77%20 Sep
0.31%22 Sep
1.22%
1.09%
1.94%
0.46%23 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.54%.

What the audience does

Likes42.3%2 031 in total
Reposts3.4%164 in total
Replies1.9%93 in total
Quotes0.3%14 in total
Bookmarks52.1%2 505 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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