Papers with Code 아카이브

Large Language Model

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

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/SalesforceAIResearch/xLAM

공식 코드

xLAM: A Family of Large Action Models to Empower AI Agent Systems

https://github.com/SamyAteia/BioRAGent

공식 코드

BioRAGent: A Retrieval-Augmented Generation System for Showcasing Generative Query Expansion and Domain-Specific Search for Scientific Q&A

https://github.com/Savannah120/alignment-handbook-PoFT

공식 코드

Preference-Oriented Supervised Fine-Tuning: Favoring Target Model Over Aligned Large Language Models

https://github.com/SeanLee97/AnglE

공식 코드

AnglE-optimized Text Embeddings

https://github.com/SensorsConnect/IoT-Agentic-Search-Engine

공식 코드

Agentic Search Engine for Real-Time IoT Data

https://github.com/SerhadS/TechNet

공식 코드

TechNet: Technology Semantic Network Based on Patent Data

https://github.com/ShayekhBinIslam/openrag

공식 코드

Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models

https://github.com/ShishirPatil/gorilla

공식 코드

Gorilla: Large Language Model Connected with Massive APIs

https://github.com/ShootingWong/DomainRAG

공식 코드

DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented Generation

https://github.com/SilinMeng0510/llm-astar

공식 코드

LLM-A*: Large Language Model Enhanced Incremental Heuristic Search on Path Planning

https://github.com/SmartDataAnalytics/KG-Copy_Network

공식 코드

Using a KG-Copy Network for Non-Goal Oriented Dialogues

https://github.com/SmartDataAnalytics/LiteralE

공식 코드

Incorporating Literals into Knowledge Graph Embeddings

https://github.com/SmartDataAnalytics/kgirnet

공식 코드

Grounding Dialogue Systems via Knowledge Graph Aware Decoding with Pre-trained Transformers

https://github.com/SonalPrabhune/RAG

공식 코드

Deploying Large Language Models With Retrieval Augmented Generation

https://github.com/SoyeonTiffanyMin/TransINT

공식 코드

TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear Subspaces

https://github.com/SqueezeAILab/SqueezedAttention

공식 코드

Squeezed Attention: Accelerating Long Context Length LLM Inference

https://github.com/Srinivas-R/AKBC-2017-Paper-14

공식 코드

Revisiting Simple Neural Networks for Learning Representations of Knowledge Graphs

https://github.com/Stanford-ILIAD/droc

공식 코드

Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections

https://github.com/StanfordAI4HI/ed-expert-simulator

공식 코드

Evaluating and Optimizing Educational Content with Large Language Model Judgments

https://github.com/StarMoonWang/SeisMoLLM

공식 코드

SeisMoLLM: Advancing Seismic Monitoring via Cross-modal Transfer with Pre-trained Large Language Model

https://github.com/StephanieWyt/HGCN-JE-JR

공식 코드

Jointly Learning Entity and Relation Representations for Entity Alignment

https://github.com/StephanieWyt/NMN

공식 코드

Neighborhood Matching Network for Entity Alignment

https://github.com/StephanieWyt/RDGCN

공식 코드

Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

https://github.com/StibiumT16/Robust-Fine-tuning

공식 코드

RbFT: Robust Fine-tuning for Retrieval-Augmented Generation against Retrieval Defects

https://github.com/TAP-LLM/SplitFedLLM

공식 코드

Safely Learning with Private Data: A Federated Learning Framework for Large Language Model

https://github.com/THU-KEG/AtomR

공식 코드

AtomR: Atomic Operator-Empowered Large Language Models for Heterogeneous Knowledge Reasoning

https://github.com/THU-KEG/KEPLER

공식 코드

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation

https://github.com/THUDM/CogKR

공식 코드

Cognitive Knowledge Graph Reasoning for One-shot Relational Learning

https://github.com/THUDM/SelfKG

공식 코드

A Self-supervised Method for Entity Alignment

https://github.com/THUIR/RuleRec

공식 코드

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

https://github.com/TRUMANCFY/MixGR

공식 코드

$\texttt{MixGR}$: Enhancing Retriever Generalization for Scientific Domain through Complementary Granularity

https://github.com/TTsamurai/LLMAdvisor_supplementary

공식 코드

Are Generative AI Agents Effective Personalized Financial Advisors?

https://github.com/TUDB-Labs/multi-lora-fine-tune

공식 코드

mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs

https://github.com/TUM-AVS/DualAD

공식 코드

DualAD: Dual-Layer Planning for Reasoning in Autonomous Driving

https://github.com/TYZY89/EMGF

공식 코드

Extensible Multi-Granularity Fusion Network for Aspect-based Sentiment Analysis

https://github.com/TZWwww/PROPHET

공식 코드

PROPHET: An Inferable Future Forecasting Benchmark with Causal Intervened Likelihood Estimation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.