Christopher Manning, Stanford NLP
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Associate Director, Stanford Institute for Human-Centered Artificial Intelligence (HAI) Stanford NLP Group, Stanford AI Lab, HAI, Linguistics and Computer Science, Stanford University What's New? We held a 25th Anniversary Stanford NLP Reunion in October 2025. Our paper on hallucinating legal LLMs is o
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第80回知è˜ãƒ™ãƒ¼ã‚¹ã‚·ã‚¹ãƒ†ãƒ ç ”ç©¶ä¼šã‚’é–‹å‚¬ã—ãŸãŒï¼ŒäºŒæ—¥é–“ã§58åã®æ–¹ã€…ã«å‚åŠ ã—ã¦é ‚ã，ç©æ¥µçš„ã«è°è«–ã«åŠ ã‚ã£ã¦é ‚ã„ãŸï¼Žã“ã®å ´ã‚’借りã¦ï¼Œå‚åŠ ã—ã¦ãã‚ŒãŸæ–¹ã€…ã«æ„Ÿè¬ã—ãŸã„．大変é…ããªã£ãŸï¼ˆçˆ†ï¼‰ãŒï¼ŒGoogleã®å·¥è—¤æ‹“æ°ã«ã‚ˆã‚‹æ‹›å¾…講演「大è¦æ¨¡ãƒ†ã‚スト処ç†ã‚’支ãˆã‚‹å½¢æ…‹ç´ 解æžæŠ€è¡“ã€ã®æ¦‚è¦ã‚’，ã“ã®ãƒ–ãƒã‚°ã§å ±å‘Šã—ã¦ãŠããŸã„．工藤æ°ã®å°‚門分野ã¯çµ±è¨ˆçš„自然言語処ç†ã¨æ©Ÿæ¢°å¦ç¿’ã§ã‚ã‚‹ãŒï¼Œæ—¥æœ¬èªžå½¢æ…‹ç´ 解æžã‚¨ãƒ³ã‚¸ãƒ³MeCabã®é–‹ç™ºè€…ã§ã‚り，他ã«ã‚‚自然言語処ç†é–¢é€£ã®æœ‰ç›Šãªãƒ„ールや，Webベースã®æ—¥æœ¬èªžå…¥åŠ›ã‚’å¯èƒ½ã«ã™ã‚‹Ajax IMEã®ã‚ˆã†ãªãƒ¦ãƒ‹ãƒ¼ã‚¯ãªã‚µãƒ¼ãƒ“スをæä¾›ã—ã¦ã„ã‚‹ãªã©ï¼Œæ™‚代をリードã™ã‚‹ç ”究開発者ã®ä¸€äººã§ã‚る．彼ã®æ´»å‹•ã«èˆˆå‘³ãŒã‚ã‚Œã°ï¼Œå½¼ã®ãƒ–ãƒã‚°ã€Œãã¾ãれ日記ã€ã¯å¿…見ã ã‚ã†ï¼Ž ãªãŠï¼Œå½“æ—¥ã¯å¼Šç¤¾å´ã®ä¸æ‰‹éš›ã§ï¼Œäºˆå®šã—ã¦ã„ãŸå·¥è—¤æ°ã®é‡è¦ãªãƒ‡ãƒ¢ã‚’ãŠã“ãªã†ã“ã¨ãŒã§ããªã‹ã£ãŸï¼Žå¼Šç¤¾ã¯ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ä¼šç¤¾ã§ã‚ã‚‹ã«ã‚‚ã‹ã‹ã‚らãšï¼Œãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯
ryan mcdonald
I am interested in language technologies. The core algorithms and models used in intelligent agents, machine translation and information retrieval and synthesis. Currently I am investing in and consulting with various AI companies in areas ranging from scientific simulation to autonomous task solving. Previously, I was Chief Scientist at ASAPP, a research scientist at Google and I completed my PhD
Google N-Gram-Patterns
Google N-Gram-Patterns General Description: This project seeks to build a co-occurrence network based on n-gram data provided by Google Inc.This project presents an easy and fast way to analyze Google n-gram data, which is contributed by Google Inc. Google n-gram data consists of a huge amount of word information based on real life searching queries entered by internet users. The huge amount of da
the Voynich Manchuscript a mystery
The Natural Language Group at the USC Information Sciences Institute conducts research in natural language processing and computational linguistics, developing new linguistic and mathematical techniques to make better technology. We have a wide range of ongoing projects, including those related to statistical machine translation, question answering, summarization, ontologies, information retrieval
Christopher Manning, Stanford NLP
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Associate Director, Stanford Institute for Human-Centered Artificial Intelligence (HAI) Stanford NLP Group, Stanford AI Lab, HAI, Linguistics and Computer Science, Stanford University What's New? We held a 25th Anniversary Stanford NLP Reunion in October 2025. Our paper on hallucinating legal LLMs is o
Dan Klein's Home Page
Some fellowships / awards: Diane S. McEntyre Award for Excellence in Teaching, 2011 UC Berkeley Distinguished Teaching Award, 2010 Jim and Donna Gray Award for Excellence in UG Teaching, 2009 Okawa Research Award, 2009 ACM Grace Murray Hopper Award, 2007 Alfred P. Sloan Fellowship, 2007 NSF CAREER Award, 2007 Microsoft Faculty Fellowship, 2005 Microsoft Graduate Fellowship, 2003 British Marshall F
Percy Liang
News I'm co-organizing a NIPS workshop on natural language processing. Research Hello! I am currently a fourth-year computer science Ph.D. student at UC Berkeley. My advisors are Michael Jordan and Dan Klein, putting me in both the statistical AI lab (SAIL) group and the Berkeley Natural Language Processing (NLP) group. I am interested in machine learning and NLP, particularly unsupervised learn
Bing Liu (Liu, Bing)'s Home Page
Research Projects Opinion Mining, Sentiment Analysis and Opinion Spam Detection (inactive) Book: Sentiment Analysis and Opinion Mining: Introduction and survey Emotional chatbot - enable chatbots or dialogue systems to converse with emotions Lifelong Machine Learning - Continual Learning. An Interview in Nature Outlook. New Survey: Continual Learning of Natural Language Processing Tasks: A Survey.
Foundations of Statistical Natural Language Processing A Case Study of Text Input System
About Distinguished Scientist & Vice President at Microsoft, IEEE Fellow, ACM Fellow, ACL Fellow, and AAIA Fellow. I am leading the Deep Learning Group at Microsoft Research. The group’s mission is to advance the state-of-the-art on deep learning and its application to natural language and image understanding, and for making progress on conversational models and methods. Our research areas are: Ne
Hal DaumII - about me
November 11, 2016 University of Utah School of Computing professor Mary Hall was awarded a $871,000 grant from the U.S. Department of Energy for an exascale computing project designed to make it easier for programmers to write code for different kinds of high-speed exascale computing systems. Her project is one of 25 software development proposals funded by the DOE it was announced Thursday, Nov.
Home - ISA-Ali
Our Java courses are 100% practical and up-to-date. You’ll learn Java Core, Maven, Git, Spring (Core, MVC, Security, Boot), Hibernate. All the essentials of the profession – and nothing unnecessary. All of our students participate in teams in real projects, remotely. You’ll sharpen your theory, gain teamwork skills, and gain practical experience for your resume.
Proxem Studio
Les solutions Proxem Studio combinent le traitement du langage naturel et les technologies de machine learning pour mieux comprendre les attentes des clients, les tendances du marché et d'autres facteurs importants, afin de garantir que les bons produits parviennent aux bonnes personnes, au bon moment. Analyse de données textuelles pour l'expérience des clients et des collaborateurs Identifiez et
MALLET homepage
MALLET is open source software [License]. For research use, please remember to cite MALLET. MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. MALLET includes sophisticated tools for document classification: efficient routines for converting text to
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Dan Jurafsky - Home Page
Photo Tourism: Microsoft Research, Interactive Visual Media Group
Tutorial Main Page - SSL Tutorial: ACL 2008
Photo Tourism: Microsoft Research, Interactive Visual Media Group
Richard Wang (王俊晴)
Percy Liang
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