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
200
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
160
文献紹介: Open Domain Web Keyphrase Extraction Beyond Language Modeling
yumeto
0
210
文献紹介: Self-Supervised_Neural_Machine_Translation
yumeto
0
140
文献紹介: Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts
yumeto
0
150
文献紹介: PAWS: Paraphrase Adversaries from Word Scrambling
yumeto
0
130
文献紹介: Beyond BLEU: Training Neural Machine Translation with Semantic Similarity
yumeto
0
250
文献紹介: EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
yumeto
0
310
文献紹介: Decomposable Neural Paraphrase Generation
yumeto
0
210
文献紹介: Analyzing the Limitations of Cross-lingual Word Embedding Mappings
yumeto
0
210
Other Decks in Research
See All in Research
公立高校入試等に対する受入保留アルゴリズム(DA)導入の提言
shunyanoda
0
380
Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment
satai
3
180
Weekly AI Agents News! 12月号 プロダクト/ニュースのアーカイブ
masatoto
0
360
クラウドのテレメトリーシステム研究動向2025年
yuukit
3
790
The many faces of AI and the role of mathematics
gpeyre
1
1.7k
DeepSeek を利用する上でのリスクと安全性の考え方
schroneko
3
1.2k
ラムダ計算の拡張に基づく 音楽プログラミング言語mimium とそのVMの実装
tomoyanonymous
0
440
博士学位論文予備審査 / Scaling Telemetry Workloads in Cloud Applications: Techniques for Instrumentation, Storage, and Mining
yuukit
1
1.8k
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications
satai
3
210
LLM 시대의 Compliance: Safety & Security
huffon
0
630
CUNY DHI_Lightning Talks_2024
digitalfellow
0
670
RapidPen: AIエージェントによるペネトレーションテスト 初期侵入全自動化の研究
laysakura
0
110
Featured
See All Featured
Fashionably flexible responsive web design (full day workshop)
malarkey
407
66k
Testing 201, or: Great Expectations
jmmastey
42
7.4k
The Invisible Side of Design
smashingmag
299
50k
Docker and Python
trallard
44
3.3k
The Myth of the Modular Monolith - Day 2 Keynote - Rails World 2024
eileencodes
22
2.6k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
40
2k
Site-Speed That Sticks
csswizardry
4
450
Into the Great Unknown - MozCon
thekraken
36
1.7k
Fontdeck: Realign not Redesign
paulrobertlloyd
83
5.5k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
29
2.5k
Let's Do A Bunch of Simple Stuff to Make Websites Faster
chriscoyier
507
140k
ReactJS: Keep Simple. Everything can be a component!
pedronauck
666
120k
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