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
240
1
Share
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
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
210
文献紹介: Open Domain Web Keyphrase Extraction Beyond Language Modeling
yumeto
0
270
文献紹介: Self-Supervised_Neural_Machine_Translation
yumeto
0
190
文献紹介: Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts
yumeto
0
200
文献紹介: PAWS: Paraphrase Adversaries from Word Scrambling
yumeto
0
190
文献紹介: Beyond BLEU: Training Neural Machine Translation with Semantic Similarity
yumeto
0
320
文献紹介: EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
yumeto
0
390
文献紹介: Decomposable Neural Paraphrase Generation
yumeto
0
250
文献紹介: Analyzing the Limitations of Cross-lingual Word Embedding Mappings
yumeto
0
270
Other Decks in Research
See All in Research
The mathematics of transformers
gpeyre
0
250
Aurora Serverless からAurora Serverless v2への課題と知見を論文から読み解く/Understanding the challenges and insights of moving from Aurora Serverless to Aurora Serverless v2 from a paper
bootjp
6
1.6k
衛星×エッジAI勉強会 衛星上におけるAI処理制約とそ取組について
satai
4
470
2026 東京科学大 情報通信系 研究室紹介 (すずかけ台)
icttitech
0
3.2k
2026.01ウェビナー資料
elith
0
350
英語教育 “研究” のあり方:学術知とアウトリーチの緊張関係
terasawat
1
930
2026年1月の生成AI領域の重要リリース&トピック解説
kajikent
0
990
進学校の生徒にはア行の苗字が多いのか
ozekinote
0
390
それ、チームの改善になってますか?ー「チームとは?」から始めた組織の実験ー
hirakawa51
0
1.1k
ローテーション別のサイドアウト戦略 ~なぜあのローテは回らないのか?~
vball_panda
0
320
Can We Teach Logical Reasoning to LLMs? – An Approach Using Synthetic Corpora (AAAI 2026 bridge keynote)
morishtr
1
220
オーストリア流 都市の公共交通サービス水準評価@公共交通オープンデータ最前線2026
trafficbrain
0
150
Featured
See All Featured
Groundhog Day: Seeking Process in Gaming for Health
codingconduct
0
170
How to audit for AI Accessibility on your Front & Back End
davetheseo
0
360
Keith and Marios Guide to Fast Websites
keithpitt
413
23k
Rails Girls Zürich Keynote
gr2m
96
14k
We Have a Design System, Now What?
morganepeng
55
8.1k
Measuring Dark Social's Impact On Conversion and Attribution
stephenakadiri
2
190
Why Our Code Smells
bkeepers
PRO
340
58k
The Hidden Cost of Media on the Web [PixelPalooza 2025]
tammyeverts
2
290
コードの90%をAIが書く世界で何が待っているのか / What awaits us in a world where 90% of the code is written by AI
rkaga
61
43k
Being A Developer After 40
akosma
91
590k
技術選定の審美眼(2025年版) / Understanding the Spiral of Technologies 2025 edition
twada
PRO
118
110k
Bridging the Design Gap: How Collaborative Modelling removes blockers to flow between stakeholders and teams @FastFlow conf
baasie
0
540
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