https://github.com/allenai/sso
공식 코드Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
Papers with Code 아카이브
Language Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/allenai/unifew
공식 코드https://github.com/allenai/unifiedqa
공식 코드UnifiedQA: Crossing Format Boundaries With a Single QA System
https://github.com/allenai/visual-reasoning-rationalization
공식 코드https://github.com/allenanzifeng/deeplearning282
공식 코드https://github.com/allenschmaltz/memory_matching
공식 코드Coarse-to-Fine Memory Matching for Joint Retrieval and Classification
https://github.com/allenschmaltz/word_ordering
공식 코드https://github.com/alontalmor/oLMpics
공식 코드https://github.com/alpha-vllm/llama2-accessory
공식 코드https://github.com/altndrr/apex
공식 코드Automatic benchmarking of large multimodal models via iterative experiment programming
https://github.com/altndrr/vic
공식 코드https://github.com/altndrr/vicss
공식 코드Vocabulary-free Image Classification and Semantic Segmentation
https://github.com/altsoph/artificial_degree_modifiers
공식 코드Connecting degree and polarity: An artificial language learning study
https://github.com/alznn/taiwanese-hokkien_mandarin_cm_dataset
공식 코드https://github.com/amaai-lab/cross-dataset-emotion-alignment
공식 코드Leveraging LLM Embeddings for Cross Dataset Label Alignment and Zero Shot Music Emotion Prediction
https://github.com/amaai-lab/jamendomaxcaps
공식 코드JamendoMaxCaps: A Large Scale Music-caption Dataset with Imputed Metadata
https://github.com/amanb2000/magic_words
공식 코드https://github.com/amazon-research/contextual-attention-nlm
공식 코드Attention-based Contextual Language Model Adaptation for Speech Recognition
https://github.com/amazon-research/datatuner
공식 코드Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity
https://github.com/amazon-research/meta-learning-the-difference
공식 코드Meta-Learning the Difference: Preparing Large Language Models for Efficient Adaptation
https://github.com/amazon-science/LC-PLM
공식 코드Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers
https://github.com/amazon-science/NARVL
공식 코드Non-autoregressive Sequence-to-Sequence Vision-Language Models
https://github.com/amazon-science/auto-rag-eval
공식 코드Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation
https://github.com/amazon-science/chronos-forecasting
공식 코드https://github.com/amazon-science/code-agent-eval
공식 코드Large Language Model Critics for Execution-Free Evaluation of Code Changes
https://github.com/amazon-science/distributionally-robust-self-supervised-learning-for-tabular-data
공식 코드Distributionally robust self-supervised learning for tabular data
https://github.com/amazon-science/graph-lm-ensemble
공식 코드An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-Commerce
https://github.com/amazon-science/llm-interpret
공식 코드https://github.com/amazon-science/masked-diffusion-lm
공식 코드A Cheaper and Better Diffusion Language Model with Soft-Masked Noise
https://github.com/amazon-science/musketeer
공식 코드Musketeer: Joint Training for Multi-task Vision Language Model with Task Explanation Prompts
https://github.com/ameet-1997/AttentionGuidance
공식 코드Guiding Attention for Self-Supervised Learning with Transformers
https://github.com/ameyagodbole/long-tail-likelihood-splits
공식 코드Benchmarking Long-tail Generalization with Likelihood Splits
https://github.com/amirabaskohi/peach
공식 코드https://github.com/amitpandey-research/complex_ner
공식 코드https://github.com/amittal151/SemEval-2021-Task4_models
공식 코드ReCAM@IITK at SemEval-2021 Task 4: BERT and ALBERT based Ensemble for Abstract Word Prediction
https://github.com/amodaresi/memllm
공식 코드MemLLM: Finetuning LLMs to Use An Explicit Read-Write Memory
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.