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Paper Digest

Knowledge graph & natural language processing platform tailored for technology domain

MISSION: Based in New York, Paper Digest has been dedicated to helping people generate meaningful contents & reason over unstructured data since 2018. Users from more than 1,500 universities and research institutions use our services daily to search, review, chat, get answers, and more.

TECHNOLOGY: Different from black-box models, our platform builds on “semantics”, which means the results are explainable. With exclusive deep learning & natural language processing (NLP) techniques,  we offer general solutions to search, summarization, conversation, question answering and content generation.

DATA & KNOWLEDGE GRAPH: We maintain our own data with real-time update. In addition to tech data (papers, patents, grants), we also store data on products, company filings, company financials & business activities (investments, m&a, etc.), people profiles, organization profiles, etc. All data is fully connected in a knowledge graph and used to infer the “missing links” between scientific & technological progresses and business & financial activities.

AI FOR TECH

Literature Review

Automatically generate reviews for any given topic.

Literature Review

Search Engine

Search & connect “dots” in technology domain.

Search Console

Question Answering

Answer science / technology questions with evidence.

Question Answering

Text Summarization

Create summaries for any English text and any domain.

Text Summarizer

PAPER DIGEST

Daily Paper Digest

Track papers by area, author, keyword and receive daily updates.

Learn More

Conference Digest

Read digests of papers & code appearing in recent conferences.

Read Digests

'Best Paper' Digest

Track the most influential papers from top conferences & journals.

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Topic Tracking

Track all new papers under a set of trending topics in real-time.

Explore Topics

SERVICES BY COLLABORATORS

Expert Search

Search for 100M experts using skill, work, name, etc.

Expert Search

Expert Review

Summarize the influential work by any tech expert.

Expert Review

Organization Search

Search 3M orgs and review related R&D, people, products.

Organization Search

Industry Review

Analyze industries by tech and discover companies behind.

Industry Review

DAILY PAPER DIGEST & HIGHLIGHTS

Track papers by area, author & keyword, and receive a one sentence summary for each paper on a daily basis

Daily Highlights (Example)

(Mavi et. al., 2022) aim to provide a general and formal definition of MHQA task, and organize and summarize existing MHQA frameworks. (Xia et. al., 2022) present a medical conversational question answering (CQA) system based on the multi-modal knowledge graph, namely “LingYi”, which is designed as a pipeline framework to maintain high flexibility. Neural passage retrieval is a new and promising approach in open retrieval question answering. (Reddy et. al., 2022) find that it lags behind standard BM25 in this important real-world setting. (Lipping et. al., 2022) introduce Clotho-AQA, a dataset for Audio question answering consisting of 1991 audio files each between 15 to 30 seconds in duration selected from the Clotho dataset [1].

TOP RESEARCH INSTITUTIONS BY AREA

Check out the top research institutions in the US by research area

LATEST POSTS

Most Influential NIPS Papers (2023-01)

The Conference on Neural Information Processing Systems (NIPS) is one of the top machine learning conferences in the world. Paper Digest Team analyzes all papers published on NIPS in the past years, and presents the 15 most influential papers for each year. This ranking list is automatically constructed based upon citations from both research papers and granted patents, and will be frequently updated to reflect the most recent changes. To browse the most productive NIPS authors by year ranked by #papers accepted, here is a list of most productive NIPS authors. To find the most influential papers from other conferences/journals, visit Best Paper Digest page. Note: the most influential papers may or may not include the papers that won the best paper awards. (Version: 2023-01)

Most Influential ICLR Papers (2023-01)

The International Conference on Learning Representations (ICLR) is one of the top machine learning conferences in the world. Paper Digest Team analyzes all papers published on ICLR in the past years, and presents the 15 most influential papers for each year. This ranking list is automatically constructed based upon citations from both research papers and granted patents, and will be frequently updated to reflect the most recent changes. To browse the most productive ICLR authors by year ranked by #papers accepted, here is a list of most productive ICLR authors. To find the most influential papers from other conferences/journals, visit Best Paper Digest page. Note: the most influential papers may or may not include the papers that won the best paper awards. (Version: 2023-01)

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