Papers with Code 아카이브
Language Acquisition
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Language acquisition refers to tasks related to the learning of a second language.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jmerullo/affordances
공식 코드Pretraining on Interactions for Learning Grounded Affordance Representations
https://github.com/kadarakos/mulisera
공식 코드https://github.com/kamperh/recipe_semantic_flickraudio
공식 코드Semantic speech retrieval with a visually grounded model of untranscribed speech
https://github.com/kamperh/recipe_vision_speech_flickr
공식 코드Visually grounded learning of keyword prediction from untranscribed speech
https://github.com/kamperh/semantic_flickraudio
공식 코드Semantic speech retrieval with a visually grounded model of untranscribed speech
https://github.com/kanishkamisra/encouraging-exposures
공식 코드https://github.com/khanhptnk/iliad
공식 코드https://github.com/marvinlvn/babyslm
공식 코드BabySLM: language-acquisition-friendly benchmark of self-supervised spoken language models
https://github.com/michaudj/languagelearner
공식 코드https://github.com/mila-iqia/babyai
공식 코드BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
https://github.com/mlieynua/sla-of-nlm
공식 코드https://github.com/modularcogsci2022/msa
공식 코드Improving Systematic Generalization Through Modularity and Augmentation
https://github.com/necla-ml/SNLI-VE
공식 코드Visual Entailment Task for Visually-Grounded Language Learning
https://github.com/neulab/tom-language-acquisition
공식 코드https://github.com/nghuyong/MTL-SLAM
공식 코드Multi-task Learning for Low-resource Second Language Acquisition Modeling
https://github.com/omriabnd/cds_syntax_semantics
공식 코드Cross-linguistically Consistent Semantic and Syntactic Annotation of Child-directed Speech
https://github.com/rehg-lab/ct-hmm
공식 코드https://github.com/salesforce/lavis
공식 코드Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
https://github.com/sjtu-compling/ZhoBLiMP
공식 코드ZhoBLiMP: a Systematic Assessment of Language Models with Linguistic Minimal Pairs in Chinese
https://github.com/slab-nlp/multimodal_clustering
공식 코드A Computational Acquisition Model for Multimodal Word Categorization
https://github.com/sled-group/TnD
공식 코드Babysit A Language Model From Scratch: Interactive Language Learning by Trials and Demonstrations
https://github.com/sled-group/comparative-learning
공식 코드Human Inspired Progressive Alignment and Comparative Learning for Grounded Word Acquisition
https://github.com/speechcog/giles_transcripts
공식 코드Age-Dependent Analysis and Stochastic Generation of Child-Directed Speech
https://github.com/suchirsalhan/mao-climb
공식 코드https://github.com/toizzy/tilt-transfer
공식 코드Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models
https://github.com/tommccoy1/meta-learning-linguistic-biases
공식 코드https://github.com/tylerachang/word-acquisition-language-models
공식 코드https://github.com/umd-psycholing/lm-syntactic-generalization
공식 코드Generalizations across filler-gap dependencies in neural language models
https://github.com/upunaprosk/small-language-models
공식 코드https://github.com/vocaliodmiku/sli-ll
공식 코드Spoken Language Intelligence of Large Language Models for Language Learning
https://github.com/vzhong/silg
공식 코드SILG: The Multi-environment Symbolic Interactive Language Grounding Benchmark
https://github.com/MathijsMul/babyai-emergent-guidance
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
https://github.com/SophiaAr/OpenAI-final-project
https://github.com/Sy-Zhang/MMC-PCFG
Learning a Grammar Inducer from Massive Uncurated Instructional Videos
https://github.com/ZHEvent/ZHEvent.github.io
Interactive Grounded Language Acquisition and Generalization in a 2D World
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.