Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/utter-project/elitr-bench
NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark
https://github.com/uw-mad-dash/pgt_index
Spatial-Temporal Large Language Model for Traffic Prediction
https://github.com/vargpt-family/vargpt-v1.1
https://github.com/vchitect/vlogger
https://github.com/vividwalker/Multi-Head-Rag
https://github.com/vlm-rl/ocean-r1
G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model
https://github.com/volcengine/verl
https://github.com/wan-video/wan2.1
https://github.com/wangclnlp/deepspeed-chat-extension
ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation
https://github.com/wdrink/simplear
Accelerating Large Language Model Decoding with Speculative Sampling
https://github.com/web-arena-x/webarena
Hierarchical Prompting Assists Large Language Model on Web Navigation
https://github.com/webis-de/acl-24
https://github.com/weixiongust/rlhf-reward-modeling
https://github.com/wellecks/llemma_formal2formal
https://github.com/wutaiqiang/shadow-ft
LLM-Neo: Parameter Efficient Knowledge Distillation for Large Language Models
https://github.com/wxh1996/VideoAgent
VideoAgent: Long-form Video Understanding with Large Language Model as Agent
https://github.com/xgenerationlab/xiyan-dbdescgen
A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL
https://github.com/xingrun-xing/spikelm
SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking
https://github.com/xmubq/dtr-text
Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data
https://github.com/yang3121099/LLM-Neo
LLM-Neo: Parameter Efficient Knowledge Distillation for Large Language Models
https://github.com/yangletliu/finlora
https://github.com/yangyijune/mma-diffusion
GuardT2I: Defending Text-to-Image Models from Adversarial Prompts
https://github.com/yangyucheng000/University/tree/main/model-1/realm
https://github.com/yangyucheng000/University/tree/main/model-3/rag
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/yangyucheng000/University/tree/main/model-3/realm
https://github.com/yangzhengyi98/dreamrec
Large Language Model Can Interpret Latent Space of Sequential Recommender
https://github.com/yaof20/real
https://github.com/yeounoh/lc_nl2sql
https://github.com/yhzhu99/medagentboard
https://github.com/ymoslem/opennmt-tutorial
Fine-tuning Large Language Models for Adaptive Machine Translation
https://github.com/youngsheen/gpst
Talk With Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction
https://github.com/yu-yang-li/starglm
Deep Learning and LLM-based Methods Applied to Stellar Lightcurve Classification
https://github.com/yuleiniu/rva
https://github.com/yuxiaw/openfactcheck
RARR: Researching and Revising What Language Models Say, Using Language Models
https://github.com/zebangcheng/emotion-llama
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.