Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Van Zuylen, Madeleine"'
Autor:
Lo, Kyle, Chang, Joseph Chee, Head, Andrew, Bragg, Jonathan, Zhang, Amy X., Trier, Cassidy, Anastasiades, Chloe, August, Tal, Authur, Russell, Bragg, Danielle, Bransom, Erin, Cachola, Isabel, Candra, Stefan, Chandrasekhar, Yoganand, Chen, Yen-Sung, Cheng, Evie Yu-Yen, Chou, Yvonne, Downey, Doug, Evans, Rob, Fok, Raymond, Hu, Fangzhou, Huff, Regan, Kang, Dongyeop, Kim, Tae Soo, Kinney, Rodney, Kittur, Aniket, Kang, Hyeonsu, Klevak, Egor, Kuehl, Bailey, Langan, Michael, Latzke, Matt, Lochner, Jaron, MacMillan, Kelsey, Marsh, Eric, Murray, Tyler, Naik, Aakanksha, Nguyen, Ngoc-Uyen, Palani, Srishti, Park, Soya, Paulic, Caroline, Rachatasumrit, Napol, Rao, Smita, Sayre, Paul, Shen, Zejiang, Siangliulue, Pao, Soldaini, Luca, Tran, Huy, van Zuylen, Madeleine, Wang, Lucy Lu, Wilhelm, Christopher, Wu, Caroline, Yang, Jiangjiang, Zamarron, Angele, Hearst, Marti A., Weld, Daniel S.
Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the need for new technology to support the reading process grow
Externí odkaz:
http://arxiv.org/abs/2303.14334
Autor:
Kinney, Rodney, Anastasiades, Chloe, Authur, Russell, Beltagy, Iz, Bragg, Jonathan, Buraczynski, Alexandra, Cachola, Isabel, Candra, Stefan, Chandrasekhar, Yoganand, Cohan, Arman, Crawford, Miles, Downey, Doug, Dunkelberger, Jason, Etzioni, Oren, Evans, Rob, Feldman, Sergey, Gorney, Joseph, Graham, David, Hu, Fangzhou, Huff, Regan, King, Daniel, Kohlmeier, Sebastian, Kuehl, Bailey, Langan, Michael, Lin, Daniel, Liu, Haokun, Lo, Kyle, Lochner, Jaron, MacMillan, Kelsey, Murray, Tyler, Newell, Chris, Rao, Smita, Rohatgi, Shaurya, Sayre, Paul, Shen, Zejiang, Singh, Amanpreet, Soldaini, Luca, Subramanian, Shivashankar, Tanaka, Amber, Wade, Alex D., Wagner, Linda, Wang, Lucy Lu, Wilhelm, Chris, Wu, Caroline, Yang, Jiangjiang, Zamarron, Angele, Van Zuylen, Madeleine, Weld, Daniel S.
The volume of scientific output is creating an urgent need for automated tools to help scientists keep up with developments in their field. Semantic Scholar (S2) is an open data platform and website aimed at accelerating science by helping scholars d
Externí odkaz:
http://arxiv.org/abs/2301.10140
Autor:
Wang, Lucy Lu, Cachola, Isabel, Bragg, Jonathan, Cheng, Evie Yu-Yen, Haupt, Chelsea, Latzke, Matt, Kuehl, Bailey, van Zuylen, Madeleine, Wagner, Linda, Weld, Daniel S.
The majority of scientific papers are distributed in PDF, which pose challenges for accessibility, especially for blind and low vision (BLV) readers. We characterize the scope of this problem by assessing the accessibility of 11,397 PDFs published 20
Externí odkaz:
http://arxiv.org/abs/2105.00076
To assess the effectiveness of any medical intervention, researchers must conduct a time-intensive and highly manual literature review. NLP systems can help to automate or assist in parts of this expensive process. In support of this goal, we release
Externí odkaz:
http://arxiv.org/abs/2104.06486
Autor:
Subramanian, Sanjay, Wang, Lucy Lu, Mehta, Sachin, Bogin, Ben, van Zuylen, Madeleine, Parasa, Sravanthi, Singh, Sameer, Gardner, Matt, Hajishirzi, Hannaneh
Understanding the relationship between figures and text is key to scientific document understanding. Medical figures in particular are quite complex, often consisting of several subfigures (75% of figures in our dataset), with detailed text describin
Externí odkaz:
http://arxiv.org/abs/2010.06000
Autor:
Hope, Tom, Amini, Aida, Wadden, David, van Zuylen, Madeleine, Parasa, Sravanthi, Horvitz, Eric, Weld, Daniel, Schwartz, Roy, Hajishirzi, Hannaneh
The COVID-19 pandemic has spawned a diverse body of scientific literature that is challenging to navigate, stimulating interest in automated tools to help find useful knowledge. We pursue the construction of a knowledge base (KB) of mechanisms -- a f
Externí odkaz:
http://arxiv.org/abs/2010.03824
Extracting information from full documents is an important problem in many domains, but most previous work focus on identifying relationships within a sentence or a paragraph. It is challenging to create a large-scale information extraction (IE) data
Externí odkaz:
http://arxiv.org/abs/2005.00512
Autor:
Wadden, David, Lin, Shanchuan, Lo, Kyle, Wang, Lucy Lu, van Zuylen, Madeleine, Cohan, Arman, Hajishirzi, Hannaneh
We introduce scientific claim verification, a new task to select abstracts from the research literature containing evidence that SUPPORTS or REFUTES a given scientific claim, and to identify rationales justifying each decision. To study this task, we
Externí odkaz:
http://arxiv.org/abs/2004.14974
Identifying the intent of a citation in scientific papers (e.g., background information, use of methods, comparing results) is critical for machine reading of individual publications and automated analysis of the scientific literature. We propose str
Externí odkaz:
http://arxiv.org/abs/1904.01608
Autor:
Ammar, Waleed, Groeneveld, Dirk, Bhagavatula, Chandra, Beltagy, Iz, Crawford, Miles, Downey, Doug, Dunkelberger, Jason, Elgohary, Ahmed, Feldman, Sergey, Ha, Vu, Kinney, Rodney, Kohlmeier, Sebastian, Lo, Kyle, Murray, Tyler, Ooi, Hsu-Han, Peters, Matthew, Power, Joanna, Skjonsberg, Sam, Wang, Lucy Lu, Wilhelm, Chris, Yuan, Zheng, van Zuylen, Madeleine, Etzioni, Oren
We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery. The resulting literature graph consists of more than 280M nodes, representing paper
Externí odkaz:
http://arxiv.org/abs/1805.02262