Papers with Code 아카이브

Knowledge Graph Completion

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 4
평가표: 7
보존된 평가 기록: 17

Knowledge graphs $G$ are represented as a collection of triples $\\{(h, r, t)\\}\subseteq E\times R\times E$, where $E$ and $R$ are the entity set and relation set. The task of Knowledge Graph Completion is to either predict unseen relations $r$ between two existing entities: $(h, ?, t)$ or predict the tail entity $t$ given the head entity and the query relation: $(h, r, ?)$.

Source: One-Shot Relational Learning for Knowledge Graphs

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/m3hrdadfi/rag-memory-interplay

공식 코드

Deciphering the Interplay of Parametric and Non-parametric Memory in Retrieval-augmented Language Models

https://github.com/m3rg-iitd/aila

공식 코드

Autonomous Microscopy Experiments through Large Language Model Agents

https://github.com/ma787639046/tdro

공식 코드

Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval

https://github.com/maarten-deraedt/idas-intent-discovery-with-abstract-summarization

공식 코드

IDAS: Intent Discovery with Abstractive Summarization

https://github.com/macaronlin/llama3-quantization

공식 코드

An empirical study of LLaMA3 quantization: from LLMs to MLLMs

https://github.com/machine-reasoning-ufrgs/spixel-gat

공식 코드

Superpixel Image Classification with Graph Attention Networks

https://github.com/maclab-hfut/psycollm

공식 코드

PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluation

https://github.com/magic-research/Sa2VA

공식 코드

4th PVUW MeViS 3rd Place Report: Sa2VA

https://github.com/maitrix-org/voila

공식 코드

Voila: Voice-Language Foundation Models for Real-Time Autonomous Interaction and Voice Role-Play

https://github.com/malek-mechergui/codemdp

공식 코드

Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch

https://github.com/malllabiisc/InteractE

공식 코드

InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions

https://github.com/malteos/pytorch-bert-document-classification

공식 코드

Enriching BERT with Knowledge Graph Embeddings for Document Classification

https://github.com/mandt-lab/knowledge-graph-tuning

공식 코드

Augmenting and Tuning Knowledge Graph Embeddings

https://github.com/mandyyyyii/scibench

공식 코드

SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models

https://github.com/manestay/borderlines

공식 코드

This Land is {Your, My} Land: Evaluating Geopolitical Biases in Language Models

https://github.com/manestay/bordirlines

공식 코드

BordIRlines: A Dataset for Evaluating Cross-lingual Retrieval-Augmented Generation

https://github.com/mangopy/direct-rag-learning

공식 코드

Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models

https://github.com/manthan2305/Efficient-G-Retriever

공식 코드

Efficient Document Retrieval with G-Retriever

https://github.com/manuelfay/llm-data-hub

공식 코드

CroissantLLM: A Truly Bilingual French-English Language Model

https://github.com/manveertamber/content_injection_attacks

공식 코드

Illusions of Relevance: Using Content Injection Attacks to Deceive Retrievers, Rerankers, and LLM Judges

https://github.com/marc1198/chat-hsr

공식 코드

LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics

https://github.com/marcosfp97/llm-binary-health-qa

공식 코드

Evaluating Search Engines and Large Language Models for Answering Health Questions

https://github.com/mariavale/contextual_inform

공식 코드

Measuring Contextual Informativeness in Child-Directed Text

https://github.com/maris205/dnahl

공식 코드

DNAHLM -- DNA sequence and Human Language mixed large language Model

https://github.com/markellekelly/ai_mental_models

공식 코드

Capturing Humans' Mental Models of AI: An Item Response Theory Approach

https://github.com/marker-inc-korea/autorag_aragog_paper

공식 코드

AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation Pipeline

https://github.com/martiansideofthemoon/rankgen

공식 코드

RankGen: Improving Text Generation with Large Ranking Models

https://github.com/martin-wey/peft-llm-code

공식 코드

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models

https://github.com/maryambrj/alien

공식 코드

Comparative Analysis of AI Agent Architectures for Entity Relationship Classification

https://github.com/mas-takayama/LLM-and-SCD/tree/main/codes

공식 코드

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach

https://github.com/mas-takayama/llm-and-scd

공식 코드

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach

https://github.com/masoud-monajati/llm_bio_ner

공식 코드

LLMs in Biomedicine: A study on clinical Named Entity Recognition

https://github.com/masterai-eam/darwin

공식 코드

DARWIN 1.5: Large Language Models as Materials Science Adapted Learners

https://github.com/matanbt/gaslite

공식 코드

GASLITEing the Retrieval: Exploring Vulnerabilities in Dense Embedding-based Search

https://github.com/matchyc/RoarGraph

공식 코드

RoarGraph: A Projected Bipartite Graph for Efficient Cross-Modal Approximate Nearest Neighbor Search

https://github.com/matsui528/lotf

공식 코드

LotusFilter: Fast Diverse Nearest Neighbor Search via a Learned Cutoff Table

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