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
Dialogue Natural Language Inference
Search
Scatter Lab Inc.
April 03, 2020
Research
2.4k
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Dialogue Natural Language Inference
Scatter Lab Inc.
April 03, 2020
More Decks by Scatter Lab Inc.
See All by Scatter Lab Inc.
zeta introduction
scatterlab
0
2k
SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
scatterlab
0
4.5k
Adversarial Filters of Dataset Biases
scatterlab
0
2.3k
Sparse, Dense, and Attentional Representations for Text Retrieval
scatterlab
0
2.4k
Weight Poisoning Attacks on Pre-trained Models
scatterlab
0
2.2k
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
scatterlab
0
2.6k
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
scatterlab
0
2.4k
Open-Retrieval Conversational Question Answering
scatterlab
0
2.4k
What Can Neural Networks Reason About?
scatterlab
0
2.3k
Other Decks in Research
See All in Research
HackSick vol.7 LT資料【LLMアーキテクチャ入門・事前学習時の躓き所解説】 スパースなAttention・状態空間モデル
rikkabotan7
0
170
[ACL 2026 Demo] Fast-MIA: Efficient and Scalable Membership Inference for LLMs
upura
0
120
高性能計算機クラスタを用いた大規模点群処理による森林の単木抽出と構造解析
kentaitakura
1
130
クラウド・AI 時代の研究開発 DX / R&D Digital Transformation
hariby
0
140
2026年 オープンキャンパス 研究室紹介
junkurihara
0
190
20260624 NLP colloquium: 単一のhubテキストがCLIPを壊す:hubnessによる埋め込みの脆弱性特定
de9uch1
2
260
第64回CV・PRML勉強会 論文紹介:Linguistic Priors for Visual Decoupling: Towards Symmetric Vision-Brain Alignment
sokikatayama
0
190
「AIとWhyを深堀る」をAIと深堀る
iflection
0
610
[最先端NLP勉強会2026] Checklists Are Better Than Reward Models For Aligning Language Models
nzw0301
1
310
JPA2026_NetworkTutorial_JunKashihara
junkashihara
0
140
typst の使い方:言語学を研究する学生のために
gitomochang
0
580
The story of RefactoringMiner. Slow research, long-term impact
tsantalis
0
150
Featured
See All Featured
Digital Ethics as a Driver of Design Innovation
axbom
PRO
1
420
エンジニアに許された特別な時間の終わり
watany
108
250k
The Illustrated Guide to Node.js - THAT Conference 2024
reverentgeek
1
470
Bash Introduction
62gerente
615
220k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
141
35k
Optimising Largest Contentful Paint
csswizardry
37
3.9k
DBのスキルで生き残る技術 - AI時代におけるテーブル設計の勘所
soudai
PRO
68
57k
The Language of Interfaces
destraynor
162
27k
Game over? The fight for quality and originality in the time of robots
wayneb77
1
270
From π to Pie charts
rasagy
0
360
10 Git Anti Patterns You Should be Aware of
lemiorhan
PRO
659
62k
Unsuck your backbone
ammeep
672
58k
Transcript
Dialogue Natural Language Inference Sean Welleck et al., ACL’19 ࢿࠁ
(ML Research Scientist, Pingpong)
ݾର ݾର 1. Dialogue Consistency and NLI 2. Dialogue NLI
Dataset 1. Triple Generation 2. Triple Annotation 3. Re-ranking with NLI 4. Evaluation 1. On Dialogue NLI 2. On Consistency in Dialogue
Dialogue Consistency and NLI Dialogue Consistency and NLI
Dialogue Consistency and NLI Dialogue Consistency and NLI • ചীࢲ
࠺ੌҙࢿ • ࢚ਵ۽ ൞ӈೞա ೠߣ ߊࢤೞݶ ఋѺ ఀ • Semanticೠ ޙਸ ݅٘ח ֢۱݅ਵ۽ח ೧Ѿ ࠛо • Natural Language Inference (NLI) • NLU, sentence representation ١ NLP ߈ਸ ੜೞӝ ਤೠ ࣻױਵ۽ॄ જ • NLI ݽ؛ downstream task ࢿמ ೱ࢚ী ӝৈ
Dialogue Consistency and NLI Dialogue Consistency and NLI • ಕܰࣗա:
ޙ ഋక۽ അ. • ചীࢲ ੌҙࢿ • ӝࠄਵ۽ Persona consistency • ֤ܻਵ۽ ߓغח ݈ ইפۄب э ࢎۈ ݈ೡ Ѫ э ঋ ޙ • : ച ղীࢲ ೠ ࢎۈ ೠ ف ݈ ߓغח • : Ӓ ࢎۈ ಕܰࣗա৬ ߓغח P = {p1 , …, pm } (uA i , uA j ) (uA i , pA k )
Dialogue Consistency and NLI
Dialogue NLI Dataset Dialogue NLI Dataset
Dialogue NLI Dataset Dialogue NLI Dataset • ߊച-ಕܰࣗա , ಕܰࣗա-ಕܰࣗա
हਵ۽ ܖয • ߊച-ߊച हب ನೣغয ਵա प ೞ ঋ (ui , pj ) (pi , pj ) (ui , uj )
Triple Generation Dialogue NLI Dataset • Triple • PersonaChatীࢲ ಕܰࣗա
ޙҗ ߊച ੌࠗ۽ Triple ۨ࠶ • ՙܻ Entailment, Neutral, Contradiction కӦ • Tripleਸ ӝળਵ۽ E, N, Cܳ ݅ٚ! • Entailment: э Tripleী ࣘೞח ف ޙՙܻ • Neutral, Contradiction: 3о ߑߨ (e1 , r, e2 ) (u, p), (p, p)
Neutral Pairs Dialogue NLI Dataset • Miscellaneous utterance যו Tripleীب
ࣘೞ ঋח ߊച ৬ ಕܰࣗա ޙ ҙ҅ח Neutral • Persona pairing Ground truth ಕܰࣗաՙܻח ࠂغѢա ݽࣽغ ঋחח ઁ ೞী э Tripleਸ ҕਬೞ ঋ ח ಕܰࣗաՙܻ Ҋ, ೞਤ ޙٜՙܻب • Relation swap ࢲ۽ ة݀ੋ ࢎपਸ աఋղח ҙ҅ ী ࣘೞח ޙٜՙܻ u p (r, r′ )
Contradiction Pairs Dialogue NLI Dataset • Relation swap ࢲ۽ ݽࣽغח
ҙ҅ ী ࣘೞח ޙٜՙܻ • Entity swap Triple ীࢲ ೧ࢲ о عਸ ٸ ݽࣽغח ҃ ف Tripleী ࣘೞח ޙٜ ՙܻ • Numeric Tripleী ನೣػ ंܳ ܲ ं۽ ߄Լࢲ ٜ݅য ޙҗ ਗې Tripleী ؍ ޙٜਸ (r, r′ ) (e1 , r, e2 ) e2 → e′ 2 (e1 , r, e′ 2 )
Triple Annotation Dialogue NLI Dataset • ಕܰࣗա ޙ →
<category> <relation> <category> ex) <person> have_pet <animal> relation , entity ա, entityח schemaী হਵݶ ੑ۱ • ٜ݅য Triple۽ ࠙ܨ ف ઑѤ ೞաܳ ݅ೞݶ 1. о sub-string 2. (e1 , r, e2 ) ∈ ℛ ∈ ℰ u ∈ U u ∈ (e1 , r, e2 ) e2 u sim(u, p) ≥ τ
Statistics Dialogue NLI Dataset • Gold-standard test set: test set
ۨ࠶ ݏҊ ೠ ࢎۈ 3ݺ 2ݺ ࢚ੋ ࢠ݅ ݽ Ѫ
Dialogue NLI Dataset
Re-ranking with NLI Re-ranking with NLI
Consistent Dialogue Agents via NLI Re-ranking with NLI •
ߊച ஏী NLI ݽ؛ ஏ Ѿҗ ഝਊ NLI ݽ؛ Contradictionۄ ౸ױೠ റࠁח confidence݅ఀ ಕօ౭ܳ ષ ࢜۽ ࣻ۽ Re-ranking
Evaluation Evaluation
On Dialogue NLI Evaluation • InferSent, ESIM ف ݽ؛ ࢎਊ
On Consistency in Dialogue Evaluation • ݽ؛ • ച ݽ؛:
Key-value memory networkܳ PersonaChatਵ۽ ण • NLI ݽ؛: ESIMਸ Dialogue NLI۽ ण • ಣо ࣇ • PersonaChatীࢲ Triple ী ೧ೞח ߊച ܳ Ҋ agent ಕܰࣗաী ী ࣘೞח ޙ ਵݶ ܳ ਵ۽ р • Entailment ޙ 10ѐ, Contradiction ޙ 10ѐ, ޙ 10ѐܳ റࠁ۽ م • ݫܼ • Hits@k, Entail@k, Contradict@k (e1 , r, e2 ) u (e1 , r, e2 ) u
Evaluation
Result Evaluation
Human Evaluation Evaluation • ParlAIܳ ా೧ w/o re-rankingҗ w/ re-rankingਸ
࠺Ү • ಣо ୋب • ݽ؛ ݃ա ಕܰࣗաܳ ੜ ߸೮חо? (1~5) • ݽ؛ п ߊചо ಕܰࣗա৬ ੌҙغחо? (0, 1) • ݽ؛ п ߊചо ݽ؛ ߊച, ݽ؛ ಕܰࣗա৬ ݽࣽغחо? (0, 1)
хࢎפ✌ ୶о ޙ ژח ҾӘೠ ݶ ઁٚ ইې োۅ۽
োۅ ࣁਃ! ࢿࠁ (ML Research Scientist, Pingpong)
[email protected]