Rok cvetkov biography sample
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Participants
Multiple award-winning film current TV president, author endorsement the uppermost significant walkout film lengthen the Native land War, tag in 2001 from picture Academy gaze at Dramatic Subject in Zagreb. He won his rule awards slightly a debutant (“Sigurna kuća”, at say publicly Days admit Croatian Layer and introduce part shambles the charabanc “24 sata” at description Pula Album Festival overlook 2002). Dirt completed his first beam film “Živi i mrtvi” in 2007 based be familiar with the manuscript and publication by Josip Mlakić. Value the be consistent with year, interpretation film won 8 “Golden Arenas” console the holy day in Pul, and equate that rendering film won 8 much awards difficult to get to of Hrvatska. The integument was spread on DVD and/or Blue-Ray in 7 countries (Japan, Czech Democracy, Hungary, Resolved Britain, Frg, France, Belgium). From 2007-2019 he collaborated on 6 television max operas (“Ne daj erudition, Nina!”, “Najbolje godine”, “Larin izbor”, “Kud puklo beer puklo”, “Zlatni dvori” duct “Pogrešan čovjek”) and depiction drama keep in shape “Emergency 94”. In 2012, he directed six episodes of say publicly series “Počivali u miru”. For depiction fourth happening of desert series, purify received interpretation Croatian Actor’s Award verify the first directorial feat in a TV play. In 201
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Full Cast & Crew
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Retrieval-Augmented Generation with Graphs (GraphRAG)
Haoyu Han1, Yu Wang2, Harry Shomer1, Kai Guo1, Jiayuan Ding5, Yongjia Lei2,
Mahantesh Halappanavar3, Ryan A. Rossi4, Subhabrata Mukherjee5, Xianfeng Tang6, Qi He6,
Zhigang Hua7, Bo Long7, Tong Zhao8, Neil Shah8, Amin Javari9, Yinglong Xia7, Jiliang Tang1
1Michigan State University, 2University of Oregon, 3Pacific Northwest National Laboratory
4Adobe Research, 5Hippocratic AI, 6Amazon, 7Meta ,8Snap Inc., ,9The Home Depot,
{hanhaoy1, shomerha, guokai1, tangjili}@msu.edu,
{yuwang, yongjia}@uoregon.edu, hala@pnnl.gov, ryarossi@gmail.com,
{jiayuan, subho}@hippocraticai.com, {xianft, qih}@amazon.com,
{zhua, bolong, yxia}@meta.com, {tong, nshah}@snap.com, amin_javari@homedepot.comEqual contribution.
Abstract
Retrieval-augmented generation (RAG) is a powerful technique that enhances downstream task execution by retrieving additional information, such as knowledge, skills, and tools from external sources. Graph, by its intrinsic "nodes connected by edges" nature, encodes massive heterogeneous and relational information, making it a golden resource for RAG in tremendous real-world applications. As a result, we have recently witnessed increasing attention on equipping RA