https://github.com/photon-git/AlloyGAN
공식 코드Inverse Materials Design by Large Language Model-Assisted Generative Framework
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
Inverse Materials Design by Large Language Model-Assisted Generative Framework
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)
Beyond In-Distribution Success: Scaling Curves of CoT Granularity for Language Model Generalization
OpenBias: Open-set Bias Detection in Text-to-Image Generative Models
Randomized Geometric Algebra Methods for Convex Neural Networks
Dependency Recurrent Neural Language Models for Sentence Completion
nanoT5: A PyTorch Framework for Pre-training and Fine-tuning T5-style Models with Limited Resources
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model
Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM
Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking
On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving
SongComposer: A Large Language Model for Lyric and Melody Generation in Song Composition
What is Wrong with Perplexity for Long-context Language Modeling?
AdaRefiner: Refining Decisions of Language Models with Adaptive Feedback
Visual Grounding for Object-Level Generalization in Reinforcement Learning
Creative Agents: Empowering Agents with Imagination for Creative Tasks
CC-Riddle: A Question Answering Dataset of Chinese Character Riddles
Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model
VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning
mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.