https://github.com/rucaibox/jiuzhang
공식 코드JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding
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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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.
JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding
Zero-shot Visual Question Answering with Language Model Feedback
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment Recommendation
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models
Exploring the Design Space of Visual Context Representation in Video MLLMs
StructGPT: A General Framework for Large Language Model to Reason over Structured Data
UFIN: Universal Feature Interaction Network for Multi-Domain Click-Through Rate Prediction
Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning
Virtual Data Augmentation: A Robust and General Framework for Fine-tuning Pre-trained Models
Virgo: A Preliminary Exploration on Reproducing o1-like MLLM
Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders
CodeS: Towards Building Open-source Language Models for Text-to-SQL
GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation
RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL
Reasoning to Attend: Try to Understand How <SEG> Token Works
NLQxform: A Language Model-based Question to SPARQL Transformer
IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact
Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Explaining Datasets in Words: Statistical Models with Natural Language Parameters
Improving Variational Autoencoder for Text Modelling with Timestep-Wise Regularisation
Large Language Model Assisted Adversarial Robustness Neural Architecture Search
Leveraging Large Language Model to Generate a Novel Metaheuristic Algorithm with CRISPE Framework
State-Free Inference of State-Space Models: The Transfer Function Approach
Cue-CoT: Chain-of-thought Prompting for Responding to In-depth Dialogue Questions with LLMs
Cue-CoT: Chain-of-thought Prompting for Responding to In-depth Dialogue Questions with LLMs
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
SemEval-2017 Task 4: Sentiment Analysis in Twitter using BERT
Fake News Detection After LLM Laundering: Measurement and Explanation
Valley: Video Assistant with Large Language model Enhanced abilitY
ChordMixer: A Scalable Neural Attention Model for Sequences with Different Lengths
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.