https://github.com/easonnie/mlp-vil
공식 코드MLP Architectures for Vision-and-Language Modeling: An Empirical Study
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A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.
Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.
Source: Wikipedia
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
MLP Architectures for Vision-and-Language Modeling: An Empirical Study
Negation Triplet Extraction with Syntactic Dependency and Semantic Consistency
MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO
Beyond Ontology in Dialogue State Tracking for Goal-Oriented Chatbot
SPA-VL: A Comprehensive Safety Preference Alignment Dataset for Vision Language Model
CXR-LLAVA: a multimodal large language model for interpreting chest X-ray images
In BLOOM: Creativity and Affinity in Artificial Lyrics and Art
DATETIME: A new benchmark to measure LLM translation and reasoning capabilities
Deep Learning and Data Augmentation for Detecting Self-Admitted Technical Debt
ALMANACS: A Simulatability Benchmark for Language Model Explainability
Learning Dynamic Author Representations with Temporal Language Models
Instruction-tuned Language Models are Better Knowledge Learners
Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees
ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain Modeling
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
SecureBERT: A Domain-Specific Language Model for Cybersecurity
G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in German
Multi-Layer Visual Feature Fusion in Multimodal LLMs: Methods, Analysis, and Best Practices
Interpretable Language Modeling via Induction-head Ngram Models
With a Little Help from my Temporal Context: Multimodal Egocentric Action Recognition
The Surprising Effectiveness of Test-Time Training for Few-Shot Learning
Training Vision-Language Models with Less Bimodal Supervision
CDF-RAG: Causal Dynamic Feedback for Adaptive Retrieval-Augmented Generation
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.