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
言語処理学会第24回年次大会 参加報告
Search
Yumeto Inaoka
March 19, 2018
Research
140
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
言語処理学会第24回年次大会 参加報告
2018/03/19の年次大会報告会で発表
Yumeto Inaoka
March 19, 2018
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
230
文献紹介: Open Domain Web Keyphrase Extraction Beyond Language Modeling
yumeto
0
290
文献紹介: Self-Supervised_Neural_Machine_Translation
yumeto
0
200
文献紹介: Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts
yumeto
0
220
文献紹介: PAWS: Paraphrase Adversaries from Word Scrambling
yumeto
0
220
文献紹介: Beyond BLEU: Training Neural Machine Translation with Semantic Similarity
yumeto
0
340
文献紹介: EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing
yumeto
0
440
文献紹介: Decomposable Neural Paraphrase Generation
yumeto
0
260
文献紹介: Analyzing the Limitations of Cross-lingual Word Embedding Mappings
yumeto
0
300
Other Decks in Research
See All in Research
PHTalks Bengaluru - SSRF When All Else Fails
dk999
0
1.2k
視覚若手の会LENSって何??
mickey_0226
0
320
Source Code Diff Revolution
tsantalis
0
170
Language and AI
ayaniwa
0
310
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
200
進化?迷走?CasualConc ファミリーアプリの現在地 @ 英語コーパス学会 2026
casualconc
0
120
[IR Reading 2026春 論文紹介] LLM-based Listwise Reranking under the Effect of Positional Bias (ECIR 2026) /IR-Reading-2026-Spring
koheishinden
PRO
0
440
2026年 オープンキャンパス 研究室紹介
junkurihara
0
220
ros2-perf-multihost: 分散システムにおける客観的なアーキテクチャ評価フレームワーク
takasehideki
0
280
[ACL 2026 Demo] Fast-MIA: Efficient and Scalable Membership Inference for LLMs
upura
0
130
適応的スパムフィルタのための軽量な類似メッセージカウンタ / jsai2026-adaptive-spam-filter
monochromegane
0
5.7k
VRID: View-Invariant Representation through Dual-Axis Transformation for Cross-iew Pose Estimation
satai
3
110
Featured
See All Featured
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
46
3k
Leveraging LLMs for student feedback in introductory data science courses - posit::conf(2025)
minecr
1
410
The Straight Up "How To Draw Better" Workshop
denniskardys
239
140k
Intergalactic Javascript Robots from Outer Space
tanoku
273
27k
What the history of the web can teach us about the future of AI
inesmontani
PRO
1
720
Ethics towards AI in product and experience design
skipperchong
2
400
Bash Introduction
62gerente
615
220k
Paper Plane
katiecoart
PRO
4
53k
Principles of Awesome APIs and How to Build Them.
keavy
128
18k
WCS-LA-2024
lcolladotor
0
840
What Being in a Rock Band Can Teach Us About Real World SEO
427marketing
0
1.1k
Building a Scalable Design System with Sketch
lauravandoore
464
34k
Transcript
ݴޠॲཧֶձ ୈ24ճ࣍େձ ࢀՃใࠂ Ԭٕज़Պֶେֶ ࣗવݴޠॲཧݚڀࣨɹҴԬເਓ
ಛʹڵຯΛऒ͔Εͨൃද ड़ޠͷ׆༻ใΛ༻͍ͨχϡʔϥϧӳ༁ ࠇᖒಓر দଜઇࡩ ࢁ؛ॣल খொक ༁ਫ਼ʹجͮ͘୯ޠΫϥεࣗಈਪఆख๏ ҆ాܓࢤ ߴҪެҰ ෦ݩ
ΠϥΫϨεύχίε ੴজ দຊҰଇ ੁ୩࢙ত χϡʔϥϧػց༁ʹ͓͚ΔڞىใΛߟྀͨ͠ޠኮબ উຢஐ দଜઇࡩ ࢁ؛ॣल খொक
ड़ޠͷ׆༻ใΛ༻͍ͨχϡʔϥϧӳ༁ ׆༻ใΛड़ޠ͔Βͯ͠ޠኮαΠζΛݮ ྫ ΕˠΔ ಈࢺɾ໋ྩܗ ޠኮΧόʔ #-&6ͱʹ্
ड़ޠͷ׆༻ใΛ༻͍ͨχϡʔϥϧӳ༁ FODPEFS EFDPEFSͷ͍ͣΕʹ͓͍ͯద༻Մೳ ˠ༁Ҏ֎ʹԠ༻Մೳ .F$BC͑͋͞Εग़དྷΔͷͰ؆୯ ˠಛʹ*1"%JDͳΒ׆༻͔Β෮ݩͰ͖Δͱͷ͜ͱ খنͳίʔύεʹ͓͍ͯಛʹޮՌ༗
༁ਫ਼ʹجͮ͘୯ޠΫϥεࣗಈਪఆख๏ ୯ޠΫϥεਪఆͷͨΊͷֶशσʔλΛର༁ίʔύε͔ΒಘΔ ˡ༁ਫ਼͕ߴ͘ͳΔΑ͏ͳ୯ޠΫϥεΛ୳͢ ࡞ֶͨ͠शσʔλ͔Β$//ʹΑΔྨثΛߏங͢Δ ྨثΛ༻͍ͨ༁Ͱ3*#&4্͕
༁ਫ਼ʹجͮ͘୯ޠΫϥεࣗಈਪఆख๏ ʮ୯ޠΫϥεʹΑΔ༁ਫ਼্ʯ͔Β ʮ༁ਫ਼͕࠷ߴͳ୯ޠΫϥεΛ୳͢ʯͱ͍͏ٯసͷൃ ର༁ίʔύε͕༁λεΫҎ֎ʹར༻Ͱ͖ΔՄೳੑ ˠίʔύεෆͩͬͨλεΫͷޫ
χϡʔϥϧػց༁ʹ͓͚ΔڞىใΛߟྀͨ͠ޠኮબ /.5ͷग़ྗ୯ޠͷީิͱͳΔޠኮαΠζΛݮΒͨ͢Ίͷ ޠኮબख๏ͷఏҊ ڞىใΛ୯ޠͷॏཁͱͯ͠ॏཁͳ୯ޠΛબ ˡ)*54ͱ͍͏ΞϧΰϦζϜΛ༻ ग़ྗະޠτʔΫϯ্ঢ͢Δ͕#-&6্
χϡʔϥϧػց༁ʹ͓͚ΔڞىใΛߟྀͨ͠ޠኮબ ༻͍ͨ)*54ΞϧΰϦζϜ8FCϖʔδͷϥϯΩϯάख๏ ˠݴޠॲཧҎ֎Ͱ༻͍ΒΕ͍ͯΔΞϧΰϦζϜ͕ ɹݴޠॲཧʹར༻Ͱ͖Δ͜ͱ͋Δ ͋ΒΏΔχϡʔϥϧจੜλεΫʹద༻Ͱ͖Δख๏ සΛجʹબ͞ΕͨޠኮਓखͰબ͞Εͨޠኮͱͷ ൺֱʹ͑Δ͔͠Εͳ͍
ൃද༰ ड़ޠͷ׆༻ใΛ༻͍ͨχϡʔϥϧӳ༁ ࠇᖒಓر দଜઇࡩ ࢁ؛ॣल খொक ༁ਫ਼ʹجͮ͘୯ޠΫϥεࣗಈਪఆख๏ ҆ాܓࢤ ߴҪެҰ ෦ݩ
ΠϥΫϨεύχίε ੴজ দຊҰଇ ੁ୩࢙ত χϡʔϥϧػց༁ʹ͓͚ΔڞىใΛߟྀͨ͠ޠኮબ উຢஐ দଜઇࡩ ࢁ؛ॣल খொक