Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
文献紹介: Query and Output: Generating Words by Que...
Search
Yumeto Inaoka
July 20, 2018
Research
210
1
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
文献紹介: Query and Output: Generating Words by Querying Distributed Word Representations for Paraphrase Generation
2018/07/20の文献紹介で発表
Yumeto Inaoka
July 20, 2018
More Decks by Yumeto Inaoka
See All by Yumeto Inaoka
文献紹介: Quantity doesn’t buy quality syntax with neural language models
yumeto
1
220
文献紹介: Open Domain Web Keyphrase Extraction Beyond Language Modeling
yumeto
0
290
文献紹介: Self-Supervised_Neural_Machine_Translation
yumeto
0
200
文献紹介: Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts
yumeto
0
210
文献紹介: PAWS: Paraphrase Adversaries from Word Scrambling
yumeto
0
220
文献紹介: Beyond BLEU: Training Neural Machine Translation with Semantic Similarity
yumeto
0
330
文献紹介: EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
yumeto
0
430
文献紹介: Decomposable Neural Paraphrase Generation
yumeto
0
260
文献紹介: Analyzing the Limitations of Cross-lingual Word Embedding Mappings
yumeto
0
290
Other Decks in Research
See All in Research
GLIM とMegaParticles:正規分布近似の限界とタイトカップリング&パーティクルフィルタの進展 / GLIM and MegaParticles : Progress of the distribution representation in SLAM
koide3
0
680
National high-resolution cropland classification of Japan with agricultural census information and multi-temporal multi-modality datasets
satai
3
420
Unified Audio Source Separation (Defense Slides)
kohei_1979
1
640
Claude Code × autoresearch 実践
mathbullet
0
230
[IR Reading 2026春 論文紹介] LLM-based Listwise Reranking under the Effect of Positional Bias (ECIR 2026) /IR-Reading-2026-Spring
koheishinden
PRO
0
300
ros2-perf-multihost: 分散システムにおける客観的なアーキテクチャ評価フレームワーク
takasehideki
0
190
第64回CV・PRML勉強会 論文紹介:Linguistic Priors for Visual Decoupling: Towards Symmetric Vision-Brain Alignment
sokikatayama
0
150
コーディングエージェントとABNを再考
hf149
2
830
NLP colloquium: AI Safety Survey
kanekomasahiro
0
930
LLM Compute Infrastructure Overview
karakurist
2
1.6k
2026年度 生成AI を活用した論文執筆ガイド/ワークショップ / 2026 Academic Year Guide to Writing Papers Using Generative AI - Workshop
ks91
PRO
0
200
シングルチャネルマルチトーカー音声認識の進展
ryomasumura
0
210
Featured
See All Featured
GraphQLとの向き合い方2022年版
quramy
50
15k
RailsConf 2023
tenderlove
30
1.5k
SEO for Brand Visibility & Recognition
aleyda
0
4.7k
The SEO Collaboration Effect
kristinabergwall1
1
520
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
10
1.3k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
49
3.5k
SEO Brein meetup: CTRL+C is not how to scale international SEO
lindahogenes
1
2.8k
Art, The Web, and Tiny UX
lynnandtonic
304
22k
Lessons Learnt from Crawling 1000+ Websites
charlesmeaden
PRO
1
1.5k
The Pragmatic Product Professional
lauravandoore
37
7.4k
Chasing Engaging Ingredients in Design
codingconduct
0
260
A Guide to Academic Writing Using Generative AI - A Workshop
ks91
PRO
1
370
Transcript
Query and Output: Generating Words by Querying Distributed Word Representations
for Paraphrase Generation Shuming Ma, Xu Sun, Wei Li, Sujian Li, Wenjie Li, Xuancheng Ren. Proceedings of NAACL-HLT 2018, pages 196-206, 2018. จݙհ Ԭٕज़Պֶେֶࣗવݴޠॲཧݚڀࣨ ҴԬເਓ
"CTUSBDU wطଘͷ4FRTFRϞσϧ͕ੜ͢Δจ จ๏తʹਖ਼͍͕͠ҙຯతʹෆదͳ͜ͱ͕Α͋͘Δ w୯ޠࢄදݱͷݕࡧʹΑͬͯ୯ޠΛੜ͢Δ 8PSE&NCFEEJOH"UUFOUJPO/FUXPSL 8&"/ ΛఏҊ wݴ͍͕͑ॏཁͳςΩετฏқԽͱจཁλεΫͰ TUBUFPGUIFBSUΛୡ
!2
*OUSPEVDUJPO w ैདྷͷ4FRTFRϞσϧ୯ޠͷҙຯͰͳ͘܇࿅ ηοτͷ୯ޠύλʔϯΛ҉ه͢Δ͕͋Δ ˡσίʔμͷग़ྗ͕ҙຯతใΛϞσϦϯά ɹ͍ͯ͠ͳ͍ͨΊ w σίʔμͷग़ྗ͕࣋ͭύϥϝʔλ͕ଟ͍ ӅΕͷ࣍ݩ͕ ޠኮαΠζ͕ສͷ߹
ύϥϝʔλ ສͱͳΔ !3
8&"/ w 8PSE&NCFEEJOH"UUFOUJPO/FUXPSL w 3//ͷग़ྗΛΫΤϦͱͯ͠࠷Ұக͢Δࢄදݱ ͷ୯ޠΛBUUFOUJPOΛ༻ͨ͠ݕࡧʹΑͬͯબ w ୯ޠͷࢄදݱΤϯίʔμɺσίʔμͷೖྗ ʹՃ͑ͯग़ྗͷΫΤϦʹΑͬͯߋ৽͞ΕΔ !4
!5 8&"/
!6 8&"/
!7 8&"/
!8 8&"/
ΫΤϦͱ୯ޠͷηοτ͔ΒείΞΛܭࢉ RUλΠϜεςοϓUͷRVFSZ FJJ൪ͷީิ୯ޠ J ʜ O OޠኮαΠζ είΞ͕࠷େͱͳΔ୯ޠΛબ WBMJEBUJPOTFUTͰͷੑೳΛجʹHFOFSBMΛ༻
!9
5SBJOJOH w ୯ޠͷબʹݕࡧΛ༻͍͍ͯΔ͕ɺҰൠతͳ 4FRTFRͱಉ༷ʹඍՄೳ ˠଛࣦؔಉ͡ͷ͕༻Մೳ w "EBN Ћ Ќ Ќ
ЏF !10
&YQFSJNFOUT 5FYU4JNQMJpDBUJPO w %BUBTFUT 1BSBMMFM8JLJQFEJB4JNQMJpDBUJPO$PSQVT 18,1 USBJOWBMJEUFTU
&OHMJTI8JLJQFEJBBOE4JNQMF&OHMJTI8JLJQFEJB &84&8 L USBJOWBMJEUFTU UFTUTFU".5ͰಘΒΕͨͭͷ3FGFSFODFΛ࣋ͭ !11
&YQFSJNFOUT 5FYU4JNQMJpDBUJPO w &WBMVBUJPO.FUSJDT #-&6 ػց༁ฏқԽͰ͘༻͍ΒΕ͍ͯΔࣗಈධՁख๏ ਓखධՁ ྲྀெੑɺଥੑɺฏқ͞ΛͰධՁ ฏқ͞ग़ྗ͕ೖྗͱൺͯͲΕ͚ͩฏқ͔Λࣔ͢
!12
݁Ռ ࣗಈධՁ !13
݁Ռ ਓखධՁ !14
"OBMZTJT w 8&"/ैདྷͷ4FRTFRͱൺͯύϥϝʔλ͕গͳ͍ !15
"OBMZTJT w /54XW1#.53ඞਢͷཁૉΛ͍͍ܽͯΔ w 4#.54"3*ྲྀெ͕ͩҙຯ͕ҟͳΔ !16
"OBMZTJT !17
"OBMZTJT !18 ˢলུ͕ଟ͘ใ͕ෆ͍ͯ͠Δ
"OBMZTJT !19 ˢTJFNFOTNBSUJO SSC TIVSCBͱ͍ͬͨແؔͷ ɹ୯ޠΛग़ྗ
"OBMZTJT !20 ˣྲྀெ͕ͩҙຯ͕ҟͳΓΑΓཧղ͕͘͠ͳ͍ͬͯΔ
$PODMVTJPO w ΫΤϦʹΑΔ୯ޠࢄදݱͷݕࡧ͔Β୯ޠΛੜ ͢ΔFODPEFSEFDPEFSGSBNFXPSLΛఏҊ w ͭͷӳޠฏқԽσʔληοτʹ͓͍ͯ ϕʔεϥΠϯͱൺֱͯ͠#-&6͕ͦΕͧΕ ͓Αͼ্ͨ͠ w ຊϞσϧTUBUFPGUIFBSUΛୡ͍ͯ͠Δ
!21