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: Similarity-Based Reconstruction Loss for ...
Search
Yumeto Inaoka
May 26, 2019
Research
1
220
文献紹介: Similarity-Based Reconstruction Loss for Meaning Representation
2019/05/28の文献紹介で発表
Yumeto Inaoka
May 26, 2019
Tweet
Share
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
190
文献紹介: Open Domain Web Keyphrase Extraction Beyond Language Modeling
yumeto
0
240
文献紹介: Self-Supervised_Neural_Machine_Translation
yumeto
0
160
文献紹介: Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts
yumeto
0
170
文献紹介: PAWS: Paraphrase Adversaries from Word Scrambling
yumeto
0
160
文献紹介: Beyond BLEU: Training Neural Machine Translation with Semantic Similarity
yumeto
0
280
文献紹介: EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
yumeto
0
350
文献紹介: Decomposable Neural Paraphrase Generation
yumeto
0
230
文献紹介: Analyzing the Limitations of Cross-lingual Word Embedding Mappings
yumeto
0
230
Other Decks in Research
See All in Research
情報技術の社会実装に向けた応用と課題:ニュースメディアの事例から / appmech-jsce 2025
upura
0
200
ip71_contraflow_reconfiguration
stkmsd
0
110
大学見本市2025 JSTさきがけ事業セミナー「顔の見えないセンシング技術:多様なセンサにもとづく個人情報に配慮した人物状態推定」
miso2024
0
160
Sat2City:3D City Generation from A Single Satellite Image with Cascaded Latent Diffusion
satai
3
110
スキマバイトサービスにおける現場起点でのデザインアプローチ
yoshioshingyouji
0
240
Vision and LanguageからのEmbodied AIとAI for Science
yushiku
PRO
1
550
Adaptive Experimental Design for Efficient Average Treatment Effect Estimation and Treatment Choice
masakat0
0
120
能動適応的実験計画
masakat0
2
840
最適化と機械学習による問題解決
mickey_kubo
0
180
「どう育てるか」より「どう働きたいか」〜スクラムマスターの最初の一歩〜
hirakawa51
0
920
RHO-1: Not All Tokens Are What You Need
sansan_randd
1
190
Towards a More Efficient Reasoning LLM: AIMO2 Solution Summary and Introduction to Fast-Math Models
analokmaus
2
880
Featured
See All Featured
The Cult of Friendly URLs
andyhume
79
6.6k
GitHub's CSS Performance
jonrohan
1032
460k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
Connecting the Dots Between Site Speed, User Experience & Your Business [WebExpo 2025]
tammyeverts
9
580
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
49
3.1k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
33
2.5k
Building Flexible Design Systems
yeseniaperezcruz
329
39k
Side Projects
sachag
455
43k
4 Signs Your Business is Dying
shpigford
185
22k
Rebuilding a faster, lazier Slack
samanthasiow
84
9.2k
YesSQL, Process and Tooling at Scale
rocio
173
14k
Facilitating Awesome Meetings
lara
56
6.6k
Transcript
Similarity-Based Reconstruction Loss for Meaning Representation
Literature 2
Abstract • • • 3
Introduction • • 4
Related Work • • • • 5
Related Work • • 6
Auto-Encoder •ℒ , • • • • 7
Weighted similarity loss •ℒ = − σ =1 sim ,
• • • : • • sim() • 8
Weighted cross-entropy loss •ℒ = − σ =1 sim ,
log( ) • • 9
Soft label loss •ℒ = − σ =1 ∗log •
∗ = ൞ sim , σ =1 sim(,) , ∈ top N 0 , ∉ top N • • 10
True-label encoding 11
Tasks & Datasets • • • 12
Results 13
Results 14
Additional Experiments • • 15
Results • • 16
Results 17
Results 18
Results 19
Discussion • • 20
Conclusion • • • • 21