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Exa API

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pip install exa_pyfrom exa_py import Exa exa = Exa("EXA_API_KEY") results = exa.search( "latest developments in ML", category="papers" )
{ "results": [ { "score": 0.1836702525615692, "title": "Asymptotically Optimal Regret for Black-Box Predict-then-Optimize", "id": "https://arxiv.org/abs/2406.07866", "url": "https://arxiv.org/abs/2406.07866", "publishedDate": "2024-06-12", "author": "Tan; Samuel; Frazier; Peter I" }, { "score": 0.18168984353542328, "title": "Machine Unlearning for Uplink Interference Cancellation", "id": "https://arxiv.org/abs/2406.05945", "url": "https://arxiv.org/abs/2406.05945", "publishedDate": "2024-06-10", "author": "Guven; Eray; Kurt; Gunes Karabulut" }, { "score": 0.17979080975055695, "title": "Attention as an RNN", "id": "https://arxiv.org/abs/2405.13956", "url": "https://arxiv.org/abs/2405.13956", "publishedDate": "2024-05-22", "author": "Feng; Leo; Tung; Frederick; Hajimirsadeghi; Hossein; Ahmed; Mohamed Osama; Bengio; Yoshua; Mori; Greg" }, { "score": 0.17959752678871155, "title": "FaithFill: Faithful Inpainting for Object Completion Using a Single Reference Image", "id": "https://arxiv.org/abs/2406.07865", "url": "https://arxiv.org/abs/2406.07865", "publishedDate": "2024-06-12", "author": "Mallick; Rupayan; Abdalla; Amr; Bargal; Sarah Adel" }, { "score": 0.17918667197227478, "title": "Talking Heads: Understanding Inter-layer Communication in Transformer Language Models", "id": "https://arxiv.org/abs/2406.09519", "url": "https://arxiv.org/abs/2406.09519", "publishedDate": "2024-06-13", "author": "Merullo; Jack; Eickhoff; Carsten; Pavlick; Ellie" }, { "score": 0.17634162306785583, "title": "FOOD: Facial Authentication and Out-of-Distribution Detection with Short-Range FMCW Radar", "id": "https://arxiv.org/abs/2406.04546", "url": "https://arxiv.org/abs/2406.04546", "publishedDate": "2024-06-06", "author": "Kahya; Sabri Mustafa; Sivrikaya; Boran Hamdi; Yavuz; Muhammet Sami; Steinbach; Eckehard" }, { "score": 0.17634151875972748, "title": "xLSTM: Extended Long Short-Term Memory", "id": "https://arxiv.org/abs/2405.04517", "url": "https://arxiv.org/abs/2405.04517", "publishedDate": "2024-05-07", "author": "Beck; Maximilian; Pöppel; Korbinian; Spanring; Markus; Auer; Andreas; Prudnikova; Oleksandra; Kopp; Michael; Klambauer; Günter; Brandstetter; Johannes; Hochreiter; Sepp" }, { "score": 0.17621161043643951, "title": "World Models with Hints of Large Language Models for Goal Achieving", "id": "https://arxiv.org/abs/2406.07381", "url": "https://arxiv.org/abs/2406.07381", "publishedDate": "2024-06-11", "author": "Liu; Zeyuan; Huan; Ziyu; Wang; Xiyao; Lyu; Jiafei; Tao; Jian; Li; Xiu; Furong; Xu; Huazhe" }, { "score": 0.17613205313682556, "title": "Deep learning classifier of locally advanced rectal cancer treatment response from endoscopy images", "id": "https://arxiv.org/abs/2405.03762", "url": "https://arxiv.org/abs/2405.03762", "publishedDate": "2024-05-06", "author": "Gomez; Jorge Tapias; Rangnekar; Aneesh; Williams; Hannah; Thompson; Garcia-Aguilar; Julio; Smith; Joshua Jesse; Veeraraghavan; Harini" }, { "score": 0.17593073844909668, "title": "MalleTrain: Deep Neural Network Training on Unfillable Supercomputer Nodes", "id": "https://arxiv.org/abs/2404.15668", "url": "https://arxiv.org/abs/2404.15668", "publishedDate": "2024-04-24", "author": "Ma; Xiaolong; Yan; Feng; Lei; Foster; Ian; Papka; Michael E; Liu; Zhengchun; Kettimuthu; Rajkumar" } ], "requestId": "abb0f98756d6c722ca35e06e0970652b" }

just a few lines of code, or integrate with:

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Exa Websets

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CEO, EvaBot

“Exa feeds our deep research AI, which helps sales people research their prospects. Without Exa's speed and quality over the web, this would be hard to pull off!”

Rabi Gupta
Rabi GuptaCEO, EvaBot
Chief scientist, Databricks

“Models are only as good as the data they're trained on, and Exa's search allowed us to get high quality data we couldn't find any other way”

Jonathan Frankle
Jonathan FrankleChief scientist, Databricks
CEO, Vercel

“This is so powerful. Exa is like Perplexity-as-a-service. The infrastructure to ground your AI products on real world data and facts.”

Guillermo Rauch
Guillermo RauchCEO, Vercel
CEO, EvaBot

“Exa feeds our deep research AI, which helps sales people research their prospects. Without Exa's speed and quality over the web, this would be hard to pull off!”

Rabi Gupta
Rabi GuptaCEO, EvaBot
Chief scientist, Databricks

“Models are only as good as the data they're trained on, and Exa's search allowed us to get high quality data we couldn't find any other way”

Jonathan Frankle
Jonathan FrankleChief scientist, Databricks
CEO, Vercel

“This is so powerful. Exa is like Perplexity-as-a-service. The infrastructure to ground your AI products on real world data and facts.”

Guillermo Rauch
Guillermo RauchCEO, Vercel