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
SSII2025 [SS1] レンズレスカメラ
ssii
PRO
2
1.1k
Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation
satai
3
210
まずはここから:Overleaf共同執筆・CopilotでAIコーディング入門・Codespacesで独立環境
matsui_528
2
590
EarthSynth: Generating Informative Earth Observation with Diffusion Models
satai
3
360
【輪講資料】Moshi: a speech-text foundation model for real-time dialogue
hpprc
3
730
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
satai
3
340
Adaptive Experimental Design for Efficient Average Treatment Effect Estimation and Treatment Choice
masakat0
0
120
最適化と機械学習による問題解決
mickey_kubo
0
180
CoRL2025速報
rpc
1
1.8k
単施設でできる臨床研究の考え方
shuntaros
0
3k
時系列データに対する解釈可能な 決定木クラスタリング
mickey_kubo
2
1k
A scalable, annual aboveground biomass product for monitoring carbon impacts of ecosystem restoration projects
satai
4
340
Featured
See All Featured
Let's Do A Bunch of Simple Stuff to Make Websites Faster
chriscoyier
507
140k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
33
2.5k
The Invisible Side of Design
smashingmag
301
51k
Git: the NoSQL Database
bkeepers
PRO
431
66k
Documentation Writing (for coders)
carmenintech
75
5k
YesSQL, Process and Tooling at Scale
rocio
173
14k
GitHub's CSS Performance
jonrohan
1032
460k
The Pragmatic Product Professional
lauravandoore
36
6.9k
Site-Speed That Sticks
csswizardry
11
880
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
132
19k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
114
20k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
31
2.5k
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