https://github.com/qwenlm/qwen-vl
공식 코드Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
Every Answer Matters: Evaluating Commonsense with Probabilistic Measures
Stateful Memory-Augmented Transformers for Efficient Dialogue Modeling
Collaborative Stance Detection via Small-Large Language Model Consistency Verification
Emotion-Aware Transformer Encoder for Empathetic Dialogue Generation
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
CTRAN: CNN-Transformer-based Network for Natural Language Understanding
Third-Party Language Model Performance Prediction from Instruction
CREAM: Consistency Regularized Self-Rewarding Language Models
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
Efficient Medical Question Answering with Knowledge-Augmented Question Generation
Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass
Bangla Grammatical Error Detection Using T5 Transformer Model
polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informatics
polyBERT: A chemical language model to enable fully machine-driven ultrafast polymer informatics
Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER
Seventeenth-Century Spanish American Notary Records for Fine-Tuning Spanish Large Language Models
Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction
TULUN: Transparent and Adaptable Low-resource Machine Translation
DialoKG: Knowledge-Structure Aware Task-Oriented Dialogue Generation
MDAPT: Multilingual Domain Adaptive Pretraining in a Single Model
Parameter-Efficient Conversational Recommender System as a Language Processing Task
Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.