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--></style></head><body lang=ZH-CN link=blue vlink="#954F72"><div class=WordSection1><p class=MsoNormal><span lang=EN-US>Hi Adapters, </span></p><p class=MsoNormal><span lang=EN-US> </span></p><p class=MsoNormal><span lang=EN-US>In this seminar, I</span>’<span lang=EN-US>ll introduce the paper </span>“<span lang=EN-US>Breaking NLI Systems with Sentences that Require Simple Lexical Inference (ACL 2018)</span>”<span lang=EN-US>. <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>This paper pointed out the limitation of the state-of-the-art Natural Langauge Inference (NLI) models by creating an adversarial datasets and designing thorough experiments, based on the essential analysis of the NLI problem itself. The method is simple and neat but not trivial and the results are convincing. <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US>Hope you can learn something from the talk =D<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US> <o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US>Time: Wed 4:30pm<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:12.0pt'>Venue: SEIEE 3-414<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:12.0pt'>Best regards,<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US style='font-size:12.0pt'>Hongru<o:p></o:p></span></p><p class=MsoNormal><span lang=EN-US><o:p> </o:p></span></p><p class=MsoNormal>发送自<span lang=EN-US> Windows 10 </span>版<span lang=EN-US><a href="https://go.microsoft.com/fwlink/?LinkId=550986"><span lang=EN-US><span lang=EN-US>邮件</span></span></a></span>应用</p><p class=MsoNormal><span lang=EN-US style='font-size:12.0pt;font-family:SimSun'><o:p> </o:p></span></p></div></body></html>