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
Integrating Transformer and Paraphrase Rules for Sentence Simplification
Search
onizuka laboratory
December 18, 2018
Research
0
56
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
Tweet
Share
More Decks by onizuka laboratory
See All by onizuka laboratory
Phrase-Based & Neural Unsupervised Machine Translation
onilab
0
110
Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions
onilab
0
65
Card-660: A Reliable Evaluation Framework for Rare Word Representation Models
onilab
0
31
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification
onilab
0
98
An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation
onilab
0
48
Generating More Interesting Responses in Neural Conversation Models with Distributional Constraints
onilab
0
98
Modeling Multi-turn Conversation with Deep Utterance Aggregation
onilab
0
91
Learning Semantic Sentence Embeddings using Pair-wise Discriminator
onilab
0
110
SGM: Sequence Generation Model for Multi-Label Classification
onilab
0
67
Other Decks in Research
See All in Research
Introduction of NII S. Koyama's Lab (AY2024)
skoyamalab
0
110
生成AIを用いたText to SQLの最前線
masatoto
1
2.3k
Generative Spoken Dialogue Language Modeling [対話論文読み会@電通大]
yuta0306
1
130
僕たちがグラフニューラルネットワークを学ぶ理由
joisino
11
2.5k
Cross-Media Information Spaces and Architectures
signer
PRO
0
120
AIを前提とした体験の実現に向けて/toward_ai_based_experiences
monochromegane
1
240
方策の長期性能に対する効率的なオフライン評価・学習 (Long-term Off-Policy Evaluation and Learning)
usaito
PRO
2
180
Discovering Universal Geometry in Embeddings with ICA
momoseoyama
1
350
説明可能AI:代表的手法と最近の動向
yuyay
1
600
継続的な研究費獲得のための考え方
moda0
0
190
200名の育児中男性の声 「僕たちは、キャリアとライフをトレードオフにしたくない」共働き3.0世代の男性が 本当に求める働き方とは【ワーキングペアレンツの転職意識調査2023|XTalent株式会社】
xtalent
0
480
20240209 データを肴に熊本の交通を考える会「車1割削減、渋滞半減、公共交通2倍」をめざし世界に学ぼう
trafficbrain
0
830
Featured
See All Featured
Cheating the UX When There Is Nothing More to Optimize - PixelPioneers
stephaniewalter
274
13k
Building Your Own Lightsaber
phodgson
99
5.7k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
357
22k
Building Adaptive Systems
keathley
31
1.9k
How GitHub Uses GitHub to Build GitHub
holman
468
290k
Bootstrapping a Software Product
garrettdimon
PRO
302
110k
Building Effective Engineering Teams - LeadDev
addyosmani
28
1.8k
The Cost Of JavaScript in 2023
addyosmani
16
3.9k
Navigating Team Friction
lara
178
13k
How To Stay Up To Date on Web Technology
chriscoyier
782
250k
Designing with Data
zakiwarfel
96
4.8k
Designing for Performance
lara
601
67k
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