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Systematic Generalization
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gtziafas/hots
공식 코드Enhancing Interpretability and Interactivity in Robot Manipulation: A Neurosymbolic Approach
https://github.com/hjkgrp/many_body_ml
공식 코드Many-body Expansion Based Machine Learning Models for Octahedral Transition Metal Complexes
https://github.com/ibm/gcog
공식 코드On the generalization capacity of neural networks during generic multimodal reasoning
https://github.com/joeylee-rio/compgen_l2s2
공식 코드Learning to Substitute Spans towards Improving Compositional Generalization
https://github.com/koriavinash1/psa
공식 코드Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
https://github.com/lgalke/easy2deeplearn
공식 코드https://github.com/likicode/QA-generalize
공식 코드Challenges in Generalization in Open Domain Question Answering
https://github.com/mainlp/SYGAR
공식 코드https://github.com/microsoft/mttl
공식 코드https://github.com/modularcogsci2022/msa
공식 코드Improving Systematic Generalization Through Modularity and Augmentation
https://github.com/namednil/sip
공식 코드SIP: Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation
https://github.com/nhashemi202/ICMO
공식 코드Inductive Biases for Zero-shot Systematic Generalization in Language-informed Reinforcement Learning
https://github.com/owenzx/met-primaug
공식 코드Mutual Exclusivity Training and Primitive Augmentation to Induce Compositionality
https://github.com/raillab/specialization_of_neural_modules
공식 코드https://github.com/rizar/CLOSURE
공식 코드CLOSURE: Assessing Systematic Generalization of CLEVR Models
https://github.com/rizar/systematic-generalization-sqoop
공식 코드Systematic Generalization: What Is Required and Can It Be Learned?
https://github.com/robertcsordas/ndr
공식 코드The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization
https://github.com/robertcsordas/transformer_generalization
공식 코드The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers
https://github.com/shanka123/ocra
공식 코드Systematic Visual Reasoning through Object-Centric Relational Abstraction
https://github.com/shanka123/slot-abstractor
공식 코드https://github.com/shininglab/systematic-generalization-via-meaningful-learning
공식 코드https://github.com/singhgautam/slate
공식 코드https://github.com/slotabstractor/slotabstractor
공식 코드https://github.com/taewonpark/AID
공식 코드Attention-based Iterative Decomposition for Tensor Product Representation
https://github.com/taewonpark/d3
공식 코드Discrete Dictionary-based Decomposition Layer for Structured Representation Learning
https://github.com/vanessadamario/understanding_reasoning
공식 코드How Modular Should Neural Module Networks Be for Systematic Generalization?
https://github.com/verypluming/SyGNS
공식 코드SyGNS: A Systematic Generalization Testbed Based on Natural Language Semantics
https://github.com/vimalabs/VIMABench
공식 코드https://github.com/vivian1993/ncrl
공식 코드Neural Compositional Rule Learning for Knowledge Graph Reasoning
https://github.com/wellecks/symbolic_generalization
공식 코드Symbolic Brittleness in Sequence Models: on Systematic Generalization in Symbolic Mathematics
https://github.com/whieya/learning-to-compose
공식 코드Learning to Compose: Improving Object Centric Learning by Injecting Compositionality
https://github.com/ylkuo/compositional-gscan
공식 코드Compositional Networks Enable Systematic Generalization for Grounded Language Understanding
https://github.com/yuanpeng16/bcdlsg
공식 코드On a Built-in Conflict between Deep Learning and Systematic Generalization
https://github.com/BorealisAI/PROVIDE
Multi-Object Representation Learning with Iterative Variational Inference
https://github.com/BorealisAI/Spatio-Temporal
Multi-Object Representation Learning with Iterative Variational Inference
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.