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
What Can Neural Networks Reason About?
Search
Scatter Lab Inc.
May 29, 2020
Research
0
2.2k
What Can Neural Networks Reason About?
Scatter Lab Inc.
May 29, 2020
Tweet
Share
More Decks by Scatter Lab Inc.
See All by Scatter Lab Inc.
zeta introduction
scatterlab
0
1.8k
SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
scatterlab
0
4.1k
Adversarial Filters of Dataset Biases
scatterlab
0
2.2k
Sparse, Dense, and Attentional Representations for Text Retrieval
scatterlab
0
2.3k
Weight Poisoning Attacks on Pre-trained Models
scatterlab
0
2.2k
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
scatterlab
0
2.5k
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
scatterlab
0
2.3k
Open-Retrieval Conversational Question Answering
scatterlab
0
2.3k
Exploring the Limits of Transfer Learning with Unified Text-to-Text Transformer
scatterlab
0
2.2k
Other Decks in Research
See All in Research
EOGS: Gaussian Splatting for Efficient Satellite Image Photogrammetry
satai
4
510
問いを起点に、社会と共鳴する知を育む場へ
matsumoto_r
PRO
0
610
機械学習と数理最適化の融合 (MOAI) による革新
mickey_kubo
0
310
snlp2025_prevent_llm_spikes
takase
0
160
大規模な2値整数計画問題に対する 効率的な重み付き局所探索法
mickey_kubo
1
360
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
kurita
0
170
RHO-1: Not All Tokens Are What You Need
sansan_randd
1
170
言語モデルの地図:確率分布と情報幾何による類似性の可視化
shimosan
5
1.4k
最適決定木を用いた処方的価格最適化
mickey_kubo
4
1.9k
[輪講] SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
nk35jk
2
980
IMC の細かすぎる話 2025
smly
2
620
SSII2025 [SS1] レンズレスカメラ
ssii
PRO
2
1.1k
Featured
See All Featured
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
31
2.5k
Rails Girls Zürich Keynote
gr2m
95
14k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
188
55k
Why You Should Never Use an ORM
jnunemaker
PRO
59
9.5k
Raft: Consensus for Rubyists
vanstee
140
7.1k
Creating an realtime collaboration tool: Agile Flush - .NET Oxford
marcduiker
31
2.2k
Learning to Love Humans: Emotional Interface Design
aarron
273
40k
Performance Is Good for Brains [We Love Speed 2024]
tammyeverts
12
1.1k
Building Better People: How to give real-time feedback that sticks.
wjessup
368
19k
Statistics for Hackers
jakevdp
799
220k
RailsConf 2023
tenderlove
30
1.2k
The Cost Of JavaScript in 2023
addyosmani
53
8.9k
Transcript
8IBUDBOOFVSBMOFUXPSL SFBTPOBCPVU ҳ࢚ળ .-4DJFOUJTU 1JOHQPOH
ݾର ݾର • Introduction: Reasoning • Algorithmic Alignment • Conclusion
*OUSPEVDUJPO3FBTPOJOH
8IBUJT3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • “୶ܻ”
8IBUJT3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ୶ܻ: ঌҊ ח Ѫਵ۽ࠗఠ ঌ ޅೞח Ѫਸ
ࢎҊೣ • ীಘ ܻী যਃ -> ܻח یझ ࣻبীਃ -> ীಘ যו աۄী ਸө? • ࠁܳ ਸ ٸ, Ӓ ࠁ۽ࠗఠ ҙೞ ޅೠ Ѫী ೠ ࢜۽ ࠁܳ ب೧ղח স
8IBUJT3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ࠁܳ ਸ ٸ, Ӓ ࠁ۽ࠗఠ ҙೞ ޅೠ
Ѫী ೠ ࢜۽ ࠁܳ ب೧ղח স • न҃ݎ ୶ܻ ޙઁ: ࠁ/ࣁ࢚ਸ ҳઑചೞҊ Ӓ ҳઑ۽ࠗఠ Ѿҗܳ ஏೞب۾ णदఇ • GNN, Neural Symbolic Programs (Semantic Parsing), Deep Sets
%FGJOJUJPOPG3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ޛ s ∈ Sо যࢲ п
sܳ Xۄח ߭ఠ۽ അೡ ࣻ Ҋ о • ࢚ട {S1, S2, S3, …} ী ೧ࢲ ۄ߰ {y1, y2, y3, …} о ਸ ٸ • ࠁ ޅೠ ࢚ട Sী ೠ ۄ߰ yܳ بೞח ೣࣻ y=g(S)ܳ ח Ѫ ݾ
4USVDUVSFTGPS3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • Deep Sets • S = {ࡈр ҕ,
ۆ ҕ, ֢ۆ ҕ} ۄҊ о೧ࠁݶ, • ࢎۈ ੑীࢲח ࣽࢲо ࢚ҙ হ {ࡈр ҕ, ۆ ҕ, ֢ۆ ҕ} = {ۆ ҕ, ֢ۆ ҕ, ࡈр ҕ} • Permutation Invariant ೞѱ ೣࣻ gܳ ࢸ҅ೠ Ѫ Deep set • য۰ਕ ࠁ݅ Ӓր MLP MLPۄҊ ࢤп • যڃ ࣽࢲ۽ ৬ب ࢚ҙ হ
4USVDUVSFTGPS3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • GNN (Graph Neural Network) • Aggregate৬ Concatܳ
ഝਊೞৈ Graph ҳઑܳ Networkܳ അ
,JOEPG3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ٜ ୶ܻ ޙઁܳ դب৬ ౠী ٮۄࢲ ֎
о۽ ࠙ܨೣ • ా҅ ਃড (Summary Statistics): য ੑ۱ਸ ‘ࣁח’ ޙઁ • द) ز ࢎী ݻ ѐ ա? Ҋনی ѐী যڃ Ѫ ݆ա? • ҙ҅ ࢲৌ (Relational Argmax): য ੑ۱ীࢲ ࢚ ҙ҅ܳ ٮח ޙઁ • द) о ݣܻ ڄযઉ ח ޛ ह যڃ ࢝ӭੋо? • ز ۽Ӓې߁ (Dynamic Programming): Ѿҗܳ ೞݴ ಹח ޙઁ • द) ೖࠁա, ઁੌ ૣ ӡ ӝ • NP-Hard Problem: ??? • द) য ী ೧ࢲ Ӓ 0غח ࠗ࠙ ਸ ਸ ࣻ ਸө?
,JOEPG3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ٜ ୶ܻ ޙઁܳ դب৬ ౠী ٮۄࢲ ֎
о۽ ࠙ܨೣ • ా҅ ਃড (Summary Statistics): য ੑ۱ਸ ‘ࣁח’ ޙઁ • द) ز ࢎী ݻ ѐ ա? Ҋনی ѐী যڃ Ѫ ݆ա? • ҙ҅ ࢲৌ (Relational Argmax): য ੑ۱ীࢲ ࢚ ҙ҅ܳ ٮח ޙઁ • द) о ݣܻ ڄযઉ ח ޛ ह যڃ ࢝ӭੋо? • ز ۽Ӓې߁ (Dynamic Programming): Ѿҗܳ ೞݴ ಹח ޙઁ • द) ೖࠁա, ઁੌ ૣ ӡ ӝ • NP-Hard Problem: ??? • द) য ী ೧ࢲ Ӓ 0غח ࠗ࠙ ਸ ਸ ࣻ ਸө?
,JOEPG3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ٜ ୶ܻ ޙઁܳ դب৬ ౠী ٮۄࢲ ֎
о۽ ࠙ܨೣ • ా҅ ਃড (Summary Statistics): য ੑ۱ਸ ‘ࣁח’ ޙઁ • द) ز ࢎী ݻ ѐ ա? Ҋনی ѐী যڃ Ѫ ݆ա? • ҙ҅ ࢲৌ (Relational Argmax): য ੑ۱ীࢲ ࢚ ҙ҅ܳ ٮח ޙઁ • द) о ݣܻ ڄযઉ ח ޛ ह যڃ ࢝ӭੋо? • ز ۽Ӓې߁ (Dynamic Programming): Ѿҗܳ ೞݴ ಹח ޙઁ • द) ೖࠁա, ઁੌ ૣ ӡ ӝ • NP-Hard Problem: ??? • द) য ী ೧ࢲ Ӓ 0غח ࠗ࠙ ਸ ਸ ࣻ ਸө?
,JOEPG3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ٜ ୶ܻ ޙઁܳ դب৬ ౠী ٮۄࢲ ֎
о۽ ࠙ܨೣ • ా҅ ਃড (Summary Statistics): য ੑ۱ਸ ‘ࣁח’ ޙઁ • द) ز ࢎী ݻ ѐ ա? Ҋনی ѐী যڃ Ѫ ݆ա? • ҙ҅ ࢲৌ (Relational Argmax): য ੑ۱ীࢲ ࢚ ҙ҅ܳ ٮח ޙઁ • द) о ݣܻ ڄযઉ ח ޛ ह যڃ ࢝ӭੋо? • ز ۽Ӓې߁ (Dynamic Programming): Ѿҗܳ ೞݴ ಹח ޙઁ • द) ೖࠁա, ઁੌ ૣ ӡ ӝ • NP-Hard Problem: ࠺Ѿ ౚ݂ӝ҅о ೦दрী ಽ ࣻ ח ޙઁܳ ೧ ޙઁٜ۽ ೦ दрী ജਗೡ ࣻ ח • द) য ী ೧ࢲ Ӓ 0غח ࠗ࠙ ਸ ਸ ࣻ ਸө?
,JOEPG3FBTPOJOH *OUSPEVDUJPO3FBTPOJOH • ٜ п ޙઁٜী ೧ࢲ যڃ न҃ݎ ҳઑ۽
ಽ ࣻ ח ೞҊ ೞ • ా҅ ਃড (Summary Statistics): য ੑ۱ਸ ‘ࣁח’ ޙઁ • द) GNNҗ Deep Setਵ۽ח ੜ ಽ ࣻ ݅, MLP۽ח ಽӝ য۰ • ҙ҅ ࢲৌ (Relational Argmax): য ੑ۱ীࢲ ࢚ ҙ҅ܳ ٮח ޙઁ • द) GNNਵ۽ח ಽ ࣻ ݅, Deep Setਵ۽ח ಽӝ য۰ • ز ۽Ӓې߁ (Dynamic Programming): Ѿҗܳ ೞݴ ಹח ޙઁ • द) GNNਵ۽ ಽ ࣻ • NP-Hard Problem: ࠺Ѿ ౚ݂ӝ҅о ೦दрী ಽ ࣻ ח ޙઁܳ ೧ ޙઁٜ۽ ೦ दрী ജਗೡ ࣻ ח • द) Exhaustive Searchо ਃೣ
"MHPSJUIN"MJHONFOU
4USVDUVSF$PNQMFYJUZPG1SPCMFN "MHPSJUINJD"MJHONFOU • ޙઁ৬ Ӓ ޙઁܳ ಹח न҃ݎ ҳઑܳ о೧ࠁӝ
• ݅ডী ޙઁ ҳઑܳ न҃ݎ ҳઑী दఆ ࣻ ݶ?
4USVDUVSF$PNQMFYJUZPG1SPCMFN "MHPSJUINJD"MJHONFOU • ޙઁ ಽ ҙীࢲ ֤ޙ ਸ ઁೣ
4USVDUVSF$PNQMFYJUZPG1SPCMFN "MHPSJUINJD"MJHONFOU • ޙઁ ಽ ҙীࢲ ֤ޙ ਸ ઁೣ
4USVDUVSF$PNQMFYJUZPG1SPCMFN "MHPSJUINJD"MJHONFOU • ޙઁ ಽ ҙীࢲ ֤ޙਸ ਸ ઁೣ •
೧ࢳ: • ઑѤਸ ݅ೞח ޙઁח GNNਵ۽ दఆ ࣻ • Ӓ ޙઁী աఋաח ޛח ୭ Nѐө݅ оמೞҊ, • Ӓ ޙઁ ޛ ࣽࢲח ޙઁܳ ಹחؘ ޖҙೞ
4USVDUVSF$PNQMFYJUZPG1SPCMFN "MHPSJUINJD"MJHONFOU • ޙઁ ಽ ҙীࢲ ֤ޙਸ ਸ ઁೣ •
೧ࢳ: • ઑѤਸ ݅ೞח ޙઁח GNNਵ۽ दఆ ࣻ • ӒܻҊ GNN MLP۽ दఆ ࣻ
4USVDUVSF$PNQMFYJUZPG1SPCMFN "MHPSJUINJD"MJHONFOU • ޙઁ ಽ ҙীࢲ ֤ޙਸ ਸ ઁೣ •
೧ࢳ: • ઑѤਸ ݅ೞח ޙઁח GNNਵ۽ दఆ ࣻ • ӒܻҊ GNN MLP۽ दఆ ࣻ • ޙઁ: “ޙઁ ण” ҃ب Ӓۡө???
4USVDUVSF$PNQMFYJUZPG1SPCMFN "MHPSJUINJD"MJHONFOU • ޙઁ : ޙઁ णী ೧ࢲب Ӓۡө? •
೧ࠁݶ MLPח ੜ ޅ ߓח Ѫ э: ҳઑਵ۽ ޙઁܳ ୶࢚ചೞח מ۱ ࠗ೧ࢲ • GNN п ױ҅ܳ ߓ ࣻ ݅, MLPۄݶ ܖ Ѿҗޛਸ ೞա۽ ߓਕঠ ೣ
1"$-FBSOBCJMJUZBOE"MJHONFOU "MHPSJUINJD"MJHONFOU • Probably approximately correct learning (Ѣ ഛೠ ण)
• ੑ۱җ ۱हਸ ࢠ݂೧ࢲ णೞח ঌҊ્ܻਸ ࢤп೧ࠁݶ • Probably: ֫ ഛܫ۽ • Approximately Correct: ݽ؛ ী۞о Threshold ݅ੌѢ
1"$-FBSOBCJMJUZ "MHPSJUINJD"MJHONFOU • Probably approximately correct learning (Ѣ ഛೠ ण)
• ೧ࢳ: • ܻ ݽ؛ ࢠ݂ਸ ా೧ࢲ णदఆ ࣻ Ҋ о೧ࠁ (PAC ઑѤ) • Ӓ۞ݶ ী۞بܳ ઁೠೞӝ ਤ೧ࢲח ݆ ࡳইঠ ೠ (୭ࣗ M ݅ఀ ࠂب۽ ࡳইঠೣ)
1"$-FBSOBCJMJUZ "MHPSJUINJD"MJHONFOU • Probably approximately correct learning (Ѣ ഛೠ ण)
• ؊ ए ೧ࢳ: • ࢠ݂ਵ۽ णदఆ ٸ, ࢿמ ֫۰ݶ ݆ ࡳইঠೠ!
1"$-FBSOBCJMJUZ&YBNQMF "MHPSJUINJD"MJHONFOU • MLPח ݽٚ ࢎѾ җਸ ೞա ܖ۽ рೡ
ࣻ ߆ী হਵ۽
1"$-FBSOBCJMJUZ&YBNQMF "MHPSJUINJD"MJHONFOU • MLPח ݽٚ ࢎѾ җਸ ೞա ܖ۽ рೡ
ࣻ ߆ী হਵ۽ • ೧ࢳ: • MLP۽ ޙઁܳ ಽѱ दః۰ݶ • ୭ࣗೠ Layer ӝ ী ೧ ੑ۱ ରਗ ӝ ݅ఀ Ѣٟઁғೠ Ѫ • ӒѪਸ فߣ૩ Layer ӝী ೧ ғೠ Ѫ • ݅ఀ ࢠ݂೧ঠ णदఆ ࣻ ਸ Ѫ
1"$-FBSOBCJMJUZBOE"MJHONFOU "MHPSJUINJD"MJHONFOU • ݽ؛ PAC ള۲ оמ ઑѤਸ ݅ೠݶ
Alignment ܳ ࣻधਵ۽ ॶ ࣻ • ೧ࢳ: • ޙઁী ೧ࢲ Ӓ ޙઁܳ f1, f2, f3,..ਵ۽ ଂѓ ࣻ Ҋ оೞҊ • Ӓ ଂѐ ٜࠗ࠙ਸ пп न҃ݎਵ۽ दఆ ࣻ Ҋ оೞݶ • Alignment ػח Ѫ • пп ݽ؛ਸ ള۲दఆ ٸ, ӝઓী Mѐ ࡳ Ѫࠁ ѱ ࡳইب غח ҃
1"$-FBSOBCJMJUZBOE"MJHONFOU "MHPSJUINJD"MJHONFOU • ݽ؛ PAC ള۲ оמ ઑѤਸ ݅ೠݶ
Alignment ܳ ࣻधਵ۽ ॶ ࣻ • ؊ ए ೧ࢳ: • য۰ ޙઁܳ ए ࣁࠗ ޙઁ۽ ଂѐࢲ णदௌਸ ٸ, • Ӓ ए ࣁࠗ ޙઁ пп ؘఠ۽ب ੜ ߓ ࣻ ਵݶ જѷ!
#FUUFS"MJHONFOU#FUUFS(FOFSBMJ[BUJPO "MHPSJUINJD"MJHONFOU • Alignmentܳ ੜ ೡ ࣻ ח ݽ؛ ੜ
ߓ ࣻ • ઑѤਸ ݅ೠח о ೞীࢲ….
#FUUFS"MJHONFOU#FUUFS(FOFSBMJ[BUJPO "MHPSJUINJD"MJHONFOU • Alignmentܳ ੜ ೡ ࣻ ח ݽ؛ ੜ
ߓ ࣻ • ઑѤਸ ݅ೠח о ೞীࢲ….
#FUUFS"MJHONFOU#FUUFS(FOFSBMJ[BUJPO "MHPSJUINJD"MJHONFOU • Alignmentܳ ੜ ೡ ࣻ ח ݽ؛ ੜ
ߓ ࣻ • ппਸ ੜ ଂѐࢲ ߓח স ੜ ഛ݀ػݶ Ӓۧѱ ػח ܻࣗ • ցޖ োೠ ݈ੋ٠ • ܻ ҙীࢲ BERTо MLP ա LSTM ࠁ ੜೞח ਬח? • BERT ҳઑо ޙ ਫ਼ੋ ҳઑܳ ؊ Generalization ਸ ੜ ೮ӝ ٸޙ
#FUUFS"MJHONFOU#FUUFS(FOFSBMJ[BUJPO "MHPSJUINJD"MJHONFOU • Generalization ਸ ੜ ޅೞח ݽ؛ য۰ ޙઁܳ
णೞӝ য۰ • ࣘغѱ ݈ೞݶ ݽ؛ ࠂبী ٮۄ Ӓ ޙઁܳ ಽ “ल” ࠁੋח Ѫ • п ޙઁী ೠ ࢿמ
#FUUFS"MJHONFOU#FUUFS(FOFSBMJ[BUJPO "MHPSJUINJD"MJHONFOU • Generalization ਸ ੜ ޅೞח ݽ؛ য۰ ޙઁܳ
णೞӝ য۰ • ࣘغѱ ݈ೞݶ ݽ؛ ࠂبী ٮۄ Ӓ ޙઁܳ ಽ “ल” ࠁੋח Ѫ • Monster Trainer (Path Searching) ޙઁী ೠ п ݽ؛ ࢿמ
$PODMVTJPO
$PODMVTJPO $PODMVTJPO • যڃ न҃ݎ ݽ؛ਸ ഝਊ೧ࢲ যڃ ޙઁী ೧ࢲ
ಽ ٸ • Ӓ ݽ؛ ҳઑо ޙઁ ࢲࢎ ҳઑܳ ನҚೡ ࣻ যঠ ೣ • ݅ড Ӓۧ ঋݶ ই ݆ ࢠ ਃೣ = ݽ؛ ޙઁܳ ੌ߈ചೡ ࣻ হ • ࠂೠ ݽ؛ ԙ ੜ ಽח ঋ݅, рױೠ ݽ؛ ಽӝ য۰ • ܻীѱ ח दࢎ • औѱ ߓ ݽ؛, рױೠ ഋక۽ ҳࢿػ ݽ؛ য ޑೣਸ ੜ աఋյ ࣻ ਸө? • അ BERT ҳઑח ցޖ ࠂೠ Ѫ ইקө?