Academic Paper Extractor
Ọrụ ọhaneze OK
380+ Models
Enweghị akara mmiri
Enweghị mkpa ịbanye
Móòdù:
+ GPT-5, Claude, Gemini
Kpụga arXiv preprint, akwụkwọ akụkọ, mọọbụ isiokwu nke isiokwu - AI na-atụgharị ya n'ime ngwe LaTeX-flavored dị ọcha. Equations nke mathematics na-adị ka equations, multi-colon layouts na-apụta, ntụgharị ndị ahụ echekwara. Powered by Meta Nougat-base.
Ọgụgụ equations + unwinding columns... ~10 sekọnd/ihuakwụkwọ
Nkarachọ ndị ahụ
Ihenhọrọ ahụ
Token na-aga n'okpuru.
Wepụta Token
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Tinye aka ka ị nweta njikọ n'aka enyi gị ma nweta 25,000 token kwa enyi.
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Sign up free maka 30K tokens / ụbọchị + 10K bonus
Akaụntụ
Na-arụ ọrụ n'ihe ịchọrọ...
Kpụga ngwe + equations site na arXiv papers, journals, na theses. Equations nke mathematics atụgharịla ka LaTeX, multi-colon layouts a na-ewepụ, ntụgharị a na-echekwa. Powered by Meta Nougat. Free, no signup.
Etu esi eji ya Academic Paper Extractor
1
Tinye init gị
Tinye ngwe, bubata faịlụ, mọọbụ depụta ihe ịchọrọ. Achọrọ akaụntụ ọbụla.
2
Pịa mepụta
Anyị AI na-arụ ọrụ gị n'ime sekọnd na-eji ihe kacha mma open-source models.
3
Bubata na akwado
Bubata, debata, mọọbụ kesaa nsonaazụ gị. Free maka ojiji nkeonwe na nke azụmahịa.
Jiri tùlè a site na API
Megharịa ihenhọrọ a site na koodị gị. OpenAI-compatible REST endpoint, Bearer-token auth, enweghị SDK ọzọ achọrọ. Token costs match the web interface.
curl -X POST https://api.free.ai/v1/chat/ \
-H "Authorization: Bearer sk-free-..." \
-H "Content-Type: application/json" \
-d '{"model": "qwen7b", "messages": [{"role": "user", "content": "Use the Academic Paper Extractor tool on: ..."}]}'Ngwaọrụ AI n'efu dị na-emetụtara
Academic Paper Extractor — FAQ
Nwere ike ịkpụpụta akwụkwọ ọ bụla na-amụ ihe / nyocha PDF - arXiv preprint, akwụkwọ nzukọ, akwụkwọ akụkọ, isiokwu isiokwu - na AI na-agbagharị ya na ngwe LaTeX-formatted dị ọcha. Equations nke mathematics na-aga site na LaTeX dị mma, multi-colon layouts na-apụta n'ụdị ịgụ, na ndepụta ntụgharị + na-echekwa. E mepụtara ya maka ụdị akwụkwọ ndị sayensị pdftotext mangles.
Meta's Nougat-base - a vision-encoder-decoder model ejirila n'ọnụọgụgụ nde arXiv. O na-echekwa ibe PDF ọbụla dịka inyogo nakwa ihenhọrọ Markdown + LaTeX, nke bụ ihe mere equations ji banye n'ụzọ ziri ezi ọbụla mgbe ha na-egosipụta dịka raster glyphs na isi PDF.
The Docling tool (PDF ka Markdown) na-eji IBM Granite-Docling - ọsọ ọsọ, layout-aware, optimized maka n'ozuzu azụmahịa dọkumenti dị ka nkwekọrịta, ozi, nkuzi. Nougat bụ n'okporo ụzọ ma dị mma na akwụkwọ agụmakwụkwọ n'ihi na ọ bụ n'ozuzu ya na-enyocha na mathematics + multi-colon scientific layouts. Jiri Docling maka azụmahịa dọkumenti, Nougat maka nchọpụta.
Yabụ - nke ahụ bụ ihenhọrọ nke killer. Inline mathematics na-abịa n'ihu dịka `$...$`, equations ngosi dịka `$$...$$`. O nwere ike ịgụ LaTeX-render equations site na arXiv submissions NA raster equations skened site na akwụkwọ ochie. Nhazi bụ nkwalite-nhazi maka ọtụtụ akwụkwọ.
Ya - Nougat na-ewepụ ụkpụrụedemede abụọ-colom / atọ-colom n'ụzọ nkịtị n'ime usoro ngụgharị kwesịrị ekwesị. Enweghị ngwe ọzọ na-apụ n'etiti okwu n'etiti ụkpụrụedemede. Ntụziaka ụkwụ a na-ewepụ n'ime ntọaka ụkwụ na ngwụcha nke sekọnd ọbụla.
Nkọwapụta ndepụta `[12]` / `(Smith 2020)` na-adị n'ime laịị. Ndepụta ndepụta na ngwụcha na-abịa site na n'ime na-echekwa na nhazi ahụ ka ọ bụrụ nke na-adịbeghị n'ime, ka ị wee nwee ike ịkpụpụta na Zotero / Mendeley / emeredịkachọrọ nkọwapụta parser.
N'ihe banyere 8-15 sekọnd kwa peeji na H200 anyị. A na-emepe akwụkwọ 10-page conference na ~ 2 nkeji. Akwụkwọ ndekọ ndekọ (50+ peeji) na-ewe minit 8-12 - tinye ma gaa.
300 tokens kwa peeji (floor 600). A 10-page conference akwụkwọ = 3,000 tokens. A 30-page thesis isiokwu = 9,000 tokens. The ụbọchị free pool covers kasị casual research-agụ.
Pịị ya na ChatGPT/Claude maka nchịkọta akwụkwọ, mepụta RAG nkeonwe n'elu kọrpus nke akwụkwọ, achọ-semantikis nke gị na laịibụlụ, debata equations n'ụzọ ziri ezi n'ime LaTeX projects, mọọbụ gụọ akwụkwọ dịka ngwe dị mfe na ekwentị gị.
Yabụ - Nougat na-eme nzọụkwụ OCR ya. Born-digital arXiv submissions bụ ndị kasị mma (equation rendering dị ọcha); akwụkwọ ndị ochie emeredịkachọrọ na-arụ ọrụ ma ọ bụ n'ihi na nghọta ihenhọrọ dị ala. Maka ihenhọrọ ihenhọrọ kacha mma na nchọpụta, malitegharịa nchọpụta na 300+ DPI tupú ịkpọlite.
E mepụtara ya n'oge na-adịghị anya, ngwe LaTeX a na-echekwa (24h anọnimị / 7d n'efu n'oge nkwụsị nke njikọ-n'ike), isi PDF a na-ehichapụ n'oge mgbe a na-ehichapụ ya. A na-ejighị ya eme ihe maka nkuzi. /privacy/ maka ntọala zuru ezu.
Ya - POST a multipart `faịlụ` ka /v1/document/academic-pdf/. Na-eziga {text_url, peeji, nlebiri anya, token, share_url}. Bearer auth (sk-free-…) na-enye 10K free tokens/ọnwa. /api/ nwere curl ọmụmụ.
Olee otú ị ga-esi họrọ ihenhọrọ a?