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
[論紹] A Deep Ensemble Model with Slot Alignment...
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
onizuka laboratory
July 05, 2018
Research
94
1
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
[論紹] A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation
弊研究室で行なったNAACL読み会の発表資料です。
onizuka laboratory
July 05, 2018
More Decks by onizuka laboratory
See All by onizuka laboratory
Phrase-Based & Neural Unsupervised Machine Translation
onilab
0
120
Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions
onilab
0
94
Card-660: A Reliable Evaluation Framework for Rare Word Representation Models
onilab
0
44
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification
onilab
0
160
Integrating Transformer and Paraphrase Rules for Sentence Simplification
onilab
0
70
An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation
onilab
0
68
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
Other Decks in Research
See All in Research
LLM の Attention 機構まとめ — 数式・計算量・メモリ
puwaer
8
2.6k
[SNLP2026] Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
wataruuuuu
0
310
Pretrain Where? Investigating How Pretraining Data Diversity Impacts Geospatial Foundation Model Performance
satai
3
130
Cross-Media Information Spaces and Architectures
signer
PRO
0
370
実例から見るLLMのマンガ理解:実務VQAタスクによる長期的文脈と視覚情報の定性評価
kzmssk
0
110
The story of RefactoringMiner. Slow research, long-term impact
tsantalis
0
150
HackSick vol.7 LT資料【LLMアーキテクチャ入門・事前学習時の躓き所解説】 スパースなAttention・状態空間モデル
rikkabotan7
0
170
大規模言語モデルは誰を覚えているか / Who Do Large Language Models Memorize?
upura
0
170
2026年 オープンキャンパス 研究室紹介
junkurihara
0
190
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
120
COMETAを用いたデータ民主化運動の歴史
sazimai
0
240
JPA2026_NetworkTutorial_JunKashihara
junkashihara
0
140
Featured
See All Featured
Navigating the moral maze — ethical principles for Al-driven product design
skipperchong
2
520
We Analyzed 250 Million AI Search Results: Here's What I Found
joshbly
1
1.9k
Google's AI Overviews - The New Search
badams
0
1.6k
Ethics towards AI in product and experience design
skipperchong
2
370
The AI Search Optimization Roadmap by Aleyda Solis
aleyda
1
6.2k
What the history of the web can teach us about the future of AI
inesmontani
PRO
1
680
Ten Tips & Tricks for a 🌱 transition
stuffmc
0
210
Embracing the Ebb and Flow
colly
88
5.2k
Lightning Talk: Beautiful Slides for Beginners
inesmontani
PRO
2
680
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
21
1.6k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
52
6.1k
Exploring anti-patterns in Rails
aemeredith
3
500
Transcript
-
• ( ( : , • 2
• 2: , • : 2 : ( • ) 2 : : : • ): 2 2 :
• , 3 • 3 3 3 3 3 ,3
3 • : 3 3 3 • 3, 3 • 3 3 • A3 3C3
( ( ) 1 > : 4. 3 • >.
. 2:: :>- :A- 1-2:: • . > 2:: 2:: :>- : -2:: • > : 1 : > : >> 3 >>1 . 1 > . > : 1 41 : 1 . • . 1 > . 3 >>1 . 1 1 13. > :. 4
• 5 2 !" !# !$ ⋯
2 &" &'(" ⋯ &" &# &'
• 2 3 C ( 3 1 1 3 (
3 1 1 6 3 )-- 13 !" !# !$ ⋯ ) B A . 6 !" !# !$ ⋯ ⋯ ( 3 )-- 3
• 3 7 37 0 3 0 • 0 7
1 1 33 !"#$%& = ( ((* +1) . ((/ + 1) ( ∶ 1ℎ3 456738 9: ;<91; =4 >=?34 @A (* ∶ 1ℎ3 456738 9: 54B<=>4 ;<91; (/ ∶ 1ℎ3 456738 9: 9?38 >3438B13C ;<91;
• - • E D E GD 79
B • G B 2 D E • ,1 8 3067 2 7 4 48 1 I D 7D ( ) 9 B () ) ( 7 E ( ) (
• • •
• 1 0 1 0 1 • 0 0
• 1 1 , 1
• 1 2 • 2 2 • 2 2
2 2
• 1