<div dir="ltr"><div dir="ltr"><div class="gmail_default" style="font-size:small"><div class="gmail_default"><div class="gmail_default"><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Thursday, January 14th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font></font><font color="#000000" style="font-family:arial,sans-serif">Zoom Virtual Talk (</font><b style="font-family:arial,sans-serif"><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_6aa2ERkDRa2FZf-er2NklA" target="_blank">register in advance here</a></font></b><font color="#000000" style="font-family:arial,sans-serif">)</font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Wenhu Chen, UCSB</p></div><div class="gmail_default"><font face="arial, sans-serif"><br></font></div><div class="gmail_default"><font face="arial, sans-serif"><br></font></div><b>Title:</b> Knowledge-Grounded Natural Language Processing<br><br></div><div class="gmail_default"><b>Abstract: </b>One of the ultimate goals of artificial intelligence is to build a knowledgeable virtual assistant that can understand natural language queries and seek over the Web to provide information to humans. Building a virtual assistant requires the models’ capability in two aspects: 1) reasoning over the massive Web knowledge to derive supporting facts, 2) grounding on the supporting facts to generate natural language.<br><br></div><div class="gmail_default">In the first part of the talk, I will discuss how to build neural models that can automatically deduce logical rules to reason over structured web knowledge (knowledge graph). However, as the Web knowledge is highly heterogeneous and distributed in both structured and unstructured forms, using only the structured knowledge could lead to severe coverage issues. To address these issues, I will further demonstrate how to build a unified model that can reason over both structured and unstructured web knowledge and integrate their information to derive the supporting fact. In the second part of the talk, I will describe how to utilize large-scale web data to pre-train knowledge-grounded text generation models, which can generalize well to different domains to produce natural language highly consistent with the given supporting facts.<br><br></div><div class="gmail_default">Finally, I will conclude my talk by proposing future directions for knowledge-grounded natural language processing.<br><br><b>Bio: </b>Wenhu Chen is a fourth-year Ph.D. student at the University of California, Santa Barbara, advised by William Yang Wang and Xifeng Yan. His research interest covers natural language processing, deep learning, knowledge representation. Specifically, he aims at developing models that can ground and reason over external world knowledge to understand human language and communicate with humans. He is also interested in multi-modal problems like visual question answering and image/video captioning. He has interned in multiple companies including Google Research, Microsoft AI & Research, Samsung Research America, eBay Research. He publishes and serves as Program Committee for ACL, NAACL, EMNLP, ICLR, NeurIPS, and CVPR. He was recognized as the top reviewer in NeurIPS 2019. He received the WACV best-student paper honorable mention in 2021.<br><br><b>Host: </b><a href="mailto:kgimpel@ttic.edu" target="_blank"> Kevin Gimpel</a><div class="gmail_default"><br></div><div class="gmail_default"><br style="color:rgb(80,0,80)"></div></div></div><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Thu, Jan 14, 2021 at 10:00 AM Mary Marre <<a href="mailto:mmarre@ttic.edu">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Thursday, January 14th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font></font><font color="#000000" style="font-family:arial,sans-serif">Zoom Virtual Talk (</font><b style="font-family:arial,sans-serif"><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_6aa2ERkDRa2FZf-er2NklA" target="_blank">register in advance here</a></font></b><font color="#000000" style="font-family:arial,sans-serif">)</font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Wenhu Chen, UCSB</p></div><div><font face="arial, sans-serif"><br></font></div><div><font face="arial, sans-serif"><br></font></div><b>Title:</b> Knowledge-Grounded Natural Language Processing<br><br></div><div><b>Abstract: </b>One of the ultimate goals of artificial intelligence is to build a knowledgeable virtual assistant that can understand natural language queries and seek over the Web to provide information to humans. Building a virtual assistant requires the models’ capability in two aspects: 1) reasoning over the massive Web knowledge to derive supporting facts, 2) grounding on the supporting facts to generate natural language.<br><br></div><div>In the first part of the talk, I will discuss how to build neural models that can automatically deduce logical rules to reason over structured web knowledge (knowledge graph). However, as the Web knowledge is highly heterogeneous and distributed in both structured and unstructured forms, using only the structured knowledge could lead to severe coverage issues. To address these issues, I will further demonstrate how to build a unified model that can reason over both structured and unstructured web knowledge and integrate their information to derive the supporting fact. In the second part of the talk, I will describe how to utilize large-scale web data to pre-train knowledge-grounded text generation models, which can generalize well to different domains to produce natural language highly consistent with the given supporting facts.<br><br></div><div>Finally, I will conclude my talk by proposing future directions for knowledge-grounded natural language processing.<br><br><b>Bio: </b>Wenhu Chen is a fourth-year Ph.D. student at the University of California, Santa Barbara, advised by William Yang Wang and Xifeng Yan. His research interest covers natural language processing, deep learning, knowledge representation. Specifically, he aims at developing models that can ground and reason over external world knowledge to understand human language and communicate with humans. He is also interested in multi-modal problems like visual question answering and image/video captioning. He has interned in multiple companies including Google Research, Microsoft AI & Research, Samsung Research America, eBay Research. He publishes and serves as Program Committee for ACL, NAACL, EMNLP, ICLR, NeurIPS, and CVPR. He was recognized as the top reviewer in NeurIPS 2019. He received the WACV best-student paper honorable mention in 2021.<br><br><b>Host: </b><a href="mailto:kgimpel@ttic.edu" target="_blank"> Kevin Gimpel</a><div><br></div><div><br></div><div><br></div></div></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Jan 13, 2021 at 2:00 PM Mary Marre <<a href="mailto:mmarre@ttic.edu" target="_blank">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><div><div><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Thursday, January 14th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font></font><font color="#000000" style="font-family:arial,sans-serif">Zoom Virtual Talk (</font><b style="font-family:arial,sans-serif"><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_6aa2ERkDRa2FZf-er2NklA" target="_blank">register in advance here</a></font></b><font color="#000000" style="font-family:arial,sans-serif">)</font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Wenhu Chen, UCSB</p></div><div><font face="arial, sans-serif"><br></font></div><div><font face="arial, sans-serif"><br></font></div><b>Title:</b> Knowledge-Grounded Natural Language Processing<br><br></div><div><b>Abstract: </b>One of the ultimate goals of artificial intelligence is to build a knowledgeable virtual assistant that can understand natural language queries and seek over the Web to provide information to humans. Building a virtual assistant requires the models’ capability in two aspects: 1) reasoning over the massive Web knowledge to derive supporting facts, 2) grounding on the supporting facts to generate natural language.<br><br></div><div>In the first part of the talk, I will discuss how to build neural models that can automatically deduce logical rules to reason over structured web knowledge (knowledge graph). However, as the Web knowledge is highly heterogeneous and distributed in both structured and unstructured forms, using only the structured knowledge could lead to severe coverage issues. To address these issues, I will further demonstrate how to build a unified model that can reason over both structured and unstructured web knowledge and integrate their information to derive the supporting fact. In the second part of the talk, I will describe how to utilize large-scale web data to pre-train knowledge-grounded text generation models, which can generalize well to different domains to produce natural language highly consistent with the given supporting facts.<br><br></div><div>Finally, I will conclude my talk by proposing future directions for knowledge-grounded natural language processing.<br><br><b>Bio: </b>Wenhu Chen is a fourth-year Ph.D. student at the University of California, Santa Barbara, advised by William Yang Wang and Xifeng Yan. His research interest covers natural language processing, deep learning, knowledge representation. Specifically, he aims at developing models that can ground and reason over external world knowledge to understand human language and communicate with humans. He is also interested in multi-modal problems like visual question answering and image/video captioning. He has interned in multiple companies including Google Research, Microsoft AI & Research, Samsung Research America, eBay Research. He publishes and serves as Program Committee for ACL, NAACL, EMNLP, ICLR, NeurIPS, and CVPR. He was recognized as the top reviewer in NeurIPS 2019. He received the WACV best-student paper honorable mention in 2021.<br><br><b>Host: </b><a href="mailto:kgimpel@ttic.edu" target="_blank"> Kevin Gimpel</a><div><div><font face="arial, sans-serif"><br></font></div><br></div></div></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Fri, Jan 8, 2021 at 9:04 AM Mary Marre <<a href="mailto:mmarre@ttic.edu" target="_blank">mmarre@ttic.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div><div style="font-size:small"><p style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;line-height:normal;margin:0px"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>When:</b> </font></font><font style="vertical-align:inherit"><font style="vertical-align:inherit"> Thursday, January 14th at<b> 11:10 am CT</b></font></font><br></font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Where:</b> </font></font></font><font color="#000000" style="font-family:arial,sans-serif">Zoom Virtual Talk (</font><b style="font-family:arial,sans-serif"><font color="#0000ff"><a href="https://uchicagogroup.zoom.us/webinar/register/WN_6aa2ERkDRa2FZf-er2NklA" target="_blank">register in advance here</a></font></b><font color="#000000" style="font-family:arial,sans-serif">)</font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"> </font></p><p class="MsoNormal" style="margin:0in 0in 0.0001pt;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><font face="arial, sans-serif"><font style="vertical-align:inherit"><font style="vertical-align:inherit"><b>Who: </b> </font></font></font>Wenhu Chen, UCSB</p></div><div style="font-size:small"><font face="arial, sans-serif"><br></font></div><div style="font-size:small"><font face="arial, sans-serif"><br></font></div><b>Title:</b> Knowledge-Grounded Natural Language Processing<br><br></div><div><b>Abstract: </b>One of the ultimate goals of artificial intelligence is to build a knowledgeable virtual assistant that can understand natural language queries and seek over the Web to provide information to humans. Building a virtual assistant requires the models’ capability in two aspects: 1) reasoning over the massive Web knowledge to derive supporting facts, 2) grounding on the supporting facts to generate natural language.<br><br></div><div>In the first part of the talk, I will discuss how to build neural models that can automatically deduce logical rules to reason over structured web knowledge (knowledge graph). However, as the Web knowledge is highly heterogeneous and distributed in both structured and unstructured forms, using only the structured knowledge could lead to severe coverage issues. To address these issues, I will further demonstrate how to build a unified model that can reason over both structured and unstructured web knowledge and integrate their information to derive the supporting fact. In the second part of the talk, I will describe how to utilize large-scale web data to pre-train knowledge-grounded text generation models, which can generalize well to different domains to produce natural language highly consistent with the given supporting facts.<br><br></div><div>Finally, I will conclude my talk by proposing future directions for knowledge-grounded natural language processing. <br><br><b>Bio: </b>Wenhu Chen is a fourth-year Ph.D. student at the University of California, Santa Barbara, advised by William Yang Wang and Xifeng Yan. His research interest covers natural language processing, deep learning, knowledge representation. Specifically, he aims at developing models that can ground and reason over external world knowledge to understand human language and communicate with humans. He is also interested in multi-modal problems like visual question answering and image/video captioning. He has interned in multiple companies including Google Research, Microsoft AI & Research, Samsung Research America, eBay Research. He publishes and serves as Program Committee for ACL, NAACL, EMNLP, ICLR, NeurIPS, and CVPR. He was recognized as the top reviewer in NeurIPS 2019. He received the WACV best-student paper honorable mention in 2021.<br><br><b>Host: </b><a href="mailto:kgimpel@ttic.edu" target="_blank"> Kevin Gimpel</a><div><div style="font-size:small"><font face="arial, sans-serif"><br></font></div><div style="font-size:small"><font face="arial, sans-serif"><br></font></div><div style="font-size:small"><font face="arial, sans-serif"><br></font></div></div></div><div><div dir="ltr"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><font face="arial, helvetica, sans-serif">Mary C. Marre</font><div><font face="arial, helvetica, sans-serif">Faculty Administrative Support</font></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6"><b>Toyota Technological Institute</b></font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">6045 S. Kenwood Avenue</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Room 517</font></i></div><div><i><font face="arial, helvetica, sans-serif" color="#3d85c6">Chicago, IL 60637</font></i></div><div><i><font face="arial, helvetica, sans-serif">p:(773) 834-1757</font></i></div><div><i><font face="arial, helvetica, sans-serif">f: (773) 357-6970</font></i></div><div><b><i><a href="mailto:mmarre@ttic.edu" target="_blank"><font face="arial, helvetica, sans-serif">mmarre@ttic.edu</font></a></i></b></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
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