Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
Integrating Transformer and Paraphrase Rules fo...
Search
onizuka laboratory
December 18, 2018
Research
72
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Integrating Transformer and Paraphrase Rules for Sentence Simplification
弊研究室で行なったEMNLP2018読み会の発表資料です。
onizuka laboratory
December 18, 2018
More Decks by onizuka laboratory
See All by onizuka laboratory
Phrase-Based & Neural Unsupervised Machine Translation
onilab
0
130
Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions
onilab
0
100
Card-660: A Reliable Evaluation Framework for Rare Word Representation Models
onilab
0
47
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification
onilab
0
160
An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation
onilab
0
70
Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints
onilab
0
110
Modeling Multi-turn Conversation with Deep Utterance Aggregation
onilab
0
100
Learning Semantic Sentence Embeddings using Pair-wise Discriminator
onilab
0
130
SGM: Sequence Generation Model for Multi-Label Classification
onilab
0
94
Other Decks in Research
See All in Research
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
290
Prithvi-EO-2.0
satai
3
100
JICA QUEST 共創×革新プログラム Impact Report(海ノ向こうコーヒー)
ontheslope
0
840
Santé et fertilité des sols : ce que nous disent les pratiques dans les systèmes de polyculture-élevage
institutdelelevage
PRO
0
120
TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis
satai
3
120
全国町字単位空き家率推定データver1.0データ仕様
microbaseinc
0
290
ICAITD 2026 Oral Presentation
rikkabotan7
0
110
研究室単位での自律的 IPv6接続性確立に向けたAS共同運用モデルの提案と実証
reokashiwa
PRO
0
230
山中市政の総括:相反する二つの顔
sishi
0
220
Language and AI
ayaniwa
0
320
COMETAを用いたデータ民主化運動の歴史
sazimai
0
280
高性能計算機クラスタを用いた大規模点群処理による森林の単木抽出と構造解析
kentaitakura
1
150
Featured
See All Featured
Google's AI Overviews - The New Search
badams
0
1.6k
New Earth Scene 8
popppiees
4
2.7k
How To Stay Up To Date on Web Technology
chriscoyier
790
250k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
49
3.6k
4 Signs Your Business is Dying
shpigford
187
23k
Information Architects: The Missing Link in Design Systems
soysaucechin
1
1.2k
SEO for Brand Visibility & Recognition
aleyda
0
4.8k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
35
2.9k
The AI Revolution Will Not Be Monopolized: How open-source beats economies of scale, even for LLMs
inesmontani
PRO
3
3.8k
YesSQL, Process and Tooling at Scale
rocio
174
15k
How Fast Is Fast Enough? [PerfNow 2025]
tammyeverts
3
940
Designing for Performance
lara
612
70k
Transcript
% 4BORJBOH ;IBP 3VJ .FOH %BRJOH)F 4BQUPOP "OEJ 1BSNBOUP
#BNCBOH 5SBOTGPSNFSBOE1BSBQISBTF 3VMFTGPS4FOUFODF4JNQMJGJDBUJPO #ݪ େو &./-1ಡΈձʢʣ
֓ཁ l 5SBOTGPSNFSϕʔεͷΞʔΩςΫνϟ l ฏқԽݴ͍͑σʔλϕʔε 4JNQMF11%#Λ ౷߹͢Δͭͷख๏ʢ%."44ͱ %$44ʣΛఏҊ l ౷߹ͷϝϦοτͭ
◦ จฏқԽͷ405"ΑΓ༏ΕΔ ◦ ϞσϧΑΓਖ਼֬ͳฏқԽنଇΛબ͠Α͏ͱ͢Δ l ιʔείʔυެ։ ◦ IUUQTHJUIVCDPN4BORJBOHUFYU@TJNQMJGJDBUJPO
5SBOTGPSNFS l ࠨ͕Τϯίʔμ l ӈ͕σίʔμ l ଛࣦؔ "#$ = −
log , ɺݱࡏͷϞσϧͷ શͯͷύϥϝʔλ
4JNQMF11%#ͷ౷߹ l ฏқԽͷχϡʔϥϧωοτϫʔΫϞσϧͰɺ ग़ݱස͕ߴ͍ฏқԽنଇΛ܇࿅͢Δ ◦ සنଇΛϊΠζͱଊ͑ͯ͠·͏ l /.5Ͱͷॳͷ֎෦ࣝ౷߹ ◦ ֎෦ࣝΛ౷߹͢Δ4.5ฏқԽྑ͍ʢ9VFUBM
ʣ l 4JNQMF11%# ◦ 1BWMJDL FUBM ◦ ສͷنଇ
ఏҊख๏̍ɿ%$44 l %FFQ$SJUJD4FOUFODF4JNQMJGJDBUJPO.PEFM l ଛࣦؔΛमਖ਼ ◦ සنଇͷݟམͱ͠Λආ͚ΔͨΊʹɺ୯ޠͷੜ֬Λ ฏқԽ֬Ͱ࠶ॏΈ͚ l ྫ
◦ ೖྗɿUIFSFDJQJFOU PGUIFLBUF HSFFOBXBZ NFEBM ◦ ग़ྗɿUIFXJOOFS PGUIFLBUF HSFFOBXBZ NFEBM l SFDJQJFOUΛग़͠ʹ͘͘ɺ XJOOFSΛग़͘͢͠ ͳΔΑ͏ଛࣦΛฦ͍ͨ͠
%$44ͷଛࣦؔ l 012# ฏқԽنଇͷॏΈɺ Ϟσϧύϥϝʔλɺ ೖྗจ l 304543 ಛఆͷ୯ޠͷΈʹɺ"#$ =
− log , ޠኮશମʹযΛ͍ͯͯΔ ◦ ͜ΕΒͷଛࣦؔΛަޓʹ࠷খԽ͢ΔΑ͏܇࿅
ఏҊख๏̎ɿ%."44 l %FFQ.FNPSZ"VHNFOUFE4FOUFODF 4JNQMJGJDBUJPO.PEFM l %$44සنଇ͕ແࢹ͞Ε͍͢ʢ͔͠͠ ܇࿅σʔλ͕ݶΒΕΔ߹ɺසنଇॏཁʣ l ֤نଇʹෳͷΩʔόϦϡʔ༻ϝϞϦΛ༻ҙ ◦
ΩʔϕΫτϧɺίϯςΩετϕΫτϧʢΤϯίʔμͷӅΕ ঢ়ଶͱͦͷ࣌ࠁͷσίʔμӅΕঢ়ଶͷՃॏฏۉʣ ◦ όϦϡʔϕΫτϧɺग़ྗϕΫτϧ
%."44
σʔληοτ l ܇࿅ 8JLJ-BSHF ;IBOHBOE-BQBUB ◦ จର l
ݕূͱධՁɺ5VSL 9VFUBM ◦ ೖྗจʹରͯ͠ਓखͷ̔ϦϑΝϨϯεʢˠྑ࣭ʣ ◦ ݕূ༻ จରɺධՁ༻ จର l ධՁ༻ʹ /FXTFMB ͏ ◦ จର
ධՁࢦඪ l ',(-ʢจͷฏқੑʣ ◦ จͷ͞ͱޠ͔Βܭࢉ l 4"3*ʢՃɾআɾอ࣋͞Ε͍ͯΔ͔ʣ ◦ ೖྗɺग़ྗɺϦϑΝϨϯεΛൺֱ l
نଇར༻ੑʢޠኮมͷਖ਼֬ੑʣ ◦ 4"3*ʹՃͱআΛผʑʹධՁ͢Δ͕ɺ߹Θ͍ͤͨ ◦ ೖྗͱϦϑΝϨϯεΛൺֱ͠ɺฏқԽنଇΛௐͯ ͦΕʹର͢Δ QSFDJTJPOɺSFDBMMɺ'Λܭࢉ
5SBOTGPSNFSͷ݁Ռʢ5VSLʣ l ',(-ͱ 4"3*͕ 3//-45.ΑΓ༏Ε͍ͯͨ l -)͕૿Ճ͢ΔͱείΞ্͕ͬͨ
5SBOTGPSNFSͷ݁Ռʢ5VSLʣ l -)͕૿Ճ͢Δͱ ',(-ͷԼ͕Δ l 4"3*ͷอ͚࣋ͩݮগɺաʹฏқԽͯ͠͠·͏
11%#౷߹ͷ݁Ռʢ5VSLʣ
11%#౷߹ͷ݁Ռʢ5VSLʣ
11%#౷߹ͷ݁Ռʢ5VSLʣ
11%#౷߹ͷ݁Ռʢ/FXTFMBʣ