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Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/chilab1/medpix-2.0
공식 코드MedPix 2.0: A Comprehensive Multimodal Biomedical Data set for Advanced AI Applications
https://github.com/chilab1/unipagpt-23
공식 코드Unipa-GPT: Large Language Models for university-oriented QA in Italian
https://github.com/chrisliu298/llm-unlearn-eco
공식 코드Large Language Model Unlearning via Embedding-Corrupted Prompts
https://github.com/chrismun/vvllm
공식 코드LLM4VV: Developing LLM-Driven Testsuite for Compiler Validation
https://github.com/chrispapa2000/maskgst
공식 코드Masked Generative Story Transformer with Character Guidance and Caption Augmentation
https://github.com/cht619/lvshan
공식 코드https://github.com/chuangtaochen-tum/livemind
공식 코드LiveMind: Low-latency Large Language Models with Simultaneous Inference
https://github.com/chuanmeng/qpp-genre
공식 코드Query Performance Prediction using Relevance Judgments Generated by Large Language Models
https://github.com/chuanmeng/rlt4reranking
공식 코드Ranked List Truncation for Large Language Model-based Re-Ranking
https://github.com/chuhac/atm-rag
공식 코드ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator
https://github.com/cibr-okubo-lab/speechbci_2024
공식 코드https://github.com/ciol-researchlab/ukil
공식 코드Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language Modeling
https://github.com/circle-hit/moei
공식 코드https://github.com/circleradon/tokenpacker
공식 코드https://github.com/cisco-open/DeepVision/tree/main/recallm
공식 코드RecallM: An Adaptable Memory Mechanism with Temporal Understanding for Large Language Models
https://github.com/cisnlp/xampler
공식 코드XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples
https://github.com/cjx96/loid
공식 코드Enhancing Content-based Recommendation via Large Language Model
https://github.com/ckdjrkffz/layout-agent
공식 코드https://github.com/ckdjrkffz/web-page-classifier
공식 코드https://github.com/cl-premonition/premonition
공식 코드Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning
https://github.com/cl-victor1/exalt_2024_bcsz
공식 코드https://github.com/claws-lab/projection-in-mllms
공식 코드Cross-Modal Projection in Multimodal LLMs Doesn't Really Project Visual Attributes to Textual Space
https://github.com/clearloveclearlove/beat
공식 코드https://github.com/cleopatra-itn/m2sa-multimodal-multilingual-sentiment-analysis
공식 코드M2SA: Multimodal and Multilingual Model for Sentiment Analysis of Tweets
https://github.com/clin0212/hydralora
공식 코드AsymLoRA: Harmonizing Data Conflicts and Commonalities in MLLMs
https://github.com/clinicalml/TabLLM
공식 코드TabLLM: Few-shot Classification of Tabular Data with Large Language Models
https://github.com/clinicalml/onboarding_human_ai
공식 코드Effective Human-AI Teams via Learned Natural Language Rules and Onboarding
https://github.com/cloud-qu/lare
공식 코드Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning
https://github.com/cmavro/gnn-rag
공식 코드GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning
https://github.com/cmbagents/cmbagent
공식 코드Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery
https://github.com/cmubig/ccub
공식 코드https://github.com/cnfaker/llava-sp
공식 코드LLaVA-SP: Enhancing Visual Representation with Visual Spatial Tokens for MLLMs
https://github.com/cobypenso/local-differential-private-conformal-prediction
공식 코드Privacy-Preserving Conformal Prediction Under Local Differential Privacy
https://github.com/cocacola-lab/mineland
공식 코드https://github.com/code-rag-bench/code-rag-bench
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.