Papers with Code 아카이브
Large Language Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/imnearth/coat
공식 코드https://github.com/imran2205/logicrag
공식 코드https://github.com/ina-foss/is24_news_topic
공식 코드https://github.com/index-tts/index-tts
공식 코드IndexTTS: An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
https://github.com/infini-ai-lab/ape
공식 코드APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding
https://github.com/informagi/embert
공식 코드https://github.com/informalsystems/fuzzmo_use_case2
공식 코드Accessible Smart Contracts Verification: Synthesizing Formal Models with Tamed LLMs
https://github.com/ink-usc/predicting-big-bench
공식 코드How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench
https://github.com/innovatingai/automind
공식 코드AutoMind: Adaptive Knowledgeable Agent for Automated Data Science
https://github.com/intellabs/nlp-architect
공식 코드Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs
https://github.com/intellabs/rag-fit
공식 코드https://github.com/intellabs/rag-retrieval-study
공식 코드https://github.com/intelligolabs/Le-RNR-Map
공식 코드Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language
https://github.com/intellisensing/rs-agent
공식 코드RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent
https://github.com/internlm/acmetrace
공식 코드Characterization of Large Language Model Development in the Datacenter
https://github.com/internlm/huixiangdou
공식 코드https://github.com/internlm/internlm-law
공식 코드InternLM-Law: An Open Source Chinese Legal Large Language Model
https://github.com/intitni/copilotforxcode
공식 코드Contextual Augmented Multi-Model Programming (CAMP): A Hybrid Local-Cloud Copilot Framework
https://github.com/intuit-ai-research/knowledge-infused-ai/tree/main/synthetic-knowledge-ingestion
공식 코드https://github.com/invictus717/MiCo
공식 코드https://github.com/ioannis-papadimitriou/rag-playground
공식 코드https://github.com/iodike/chronokge
공식 코드Temporal Knowledge Graph Reasoning with Low-rank and Model-agnostic Representations
https://github.com/ionutiga/llms-for-kgc
공식 코드https://github.com/ipouyall/can-llms-be-lateral-thinkers
공식 코드uTeBC-NLP at SemEval-2024 Task 9: Can LLMs be Lateral Thinkers?
https://github.com/iqvianlp/llm-onto-infuse
공식 코드Towards Ontology-Enhanced Representation Learning for Large Language Models
https://github.com/iqvianlp/ontologyrag
공식 코드https://github.com/ireklos/pathe
공식 코드PathE: Leveraging Entity-Agnostic Paths for Parameter-Efficient Knowledge Graph Embeddings
https://github.com/irenamal/ec-kity
공식 코드https://github.com/irenezihuili/cgprompt
공식 코드https://github.com/irenezihuili/graphusion
공식 코드Graphusion: A RAG Framework for Knowledge Graph Construction with a Global Perspective
https://github.com/irgroup/suir
공식 코드Context-Driven Interactive Query Simulations Based on Generative Large Language Models
https://github.com/irlabamsterdam/cone-rag
공식 코드Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggets
https://github.com/irokin/GPFL
공식 코드Towards Learning Instantiated Logical Rules from Knowledge Graphs
https://github.com/irokin/RuleHierarchy
공식 코드Building Rule Hierarchies for Efficient Logical Rule Learning from Knowledge Graphs
https://github.com/isaacwasserman/LongRAG
공식 코드Enhancing Retrieval in QA Systems with Derived Feature Association
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.