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/facebookresearch/ssl-relation-prediction

공식 코드

Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations

https://github.com/facebookresearch/sweet_rl

공식 코드

SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks

https://github.com/facebookresearch/vjepa2

공식 코드

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

https://github.com/facebookresearch/zero

공식 코드

Zero-Shot Vision Encoder Grafting via LLM Surrogates

https://github.com/faisalqarah/saudibert

공식 코드

SaudiBERT: A Large Language Model Pretrained on Saudi Dialect Corpora

https://github.com/fangguo1/mcranker

공식 코드

MCRanker: Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers

https://github.com/fangshiyuu/codrivingllm

공식 코드

Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework

https://github.com/fanhaoxiang1/litlinker

공식 코드

LitLinker: Supporting the Ideation of Interdisciplinary Contexts with Large Language Models for Teaching Literature in Elementary Schools

https://github.com/fanyin3639/lid-hallucinationdetection

공식 코드

Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension

https://github.com/fardinsaad/gricean-norms

공식 코드

Gricean Norms as a Basis for Effective Collaboration

https://github.com/fate-ubw/raglab

공식 코드

RAGLAB: A Modular and Research-Oriented Unified Framework for Retrieval-Augmented Generation

https://github.com/fede-stack/adaptive-rag-for-psychological-assessment

공식 코드

Are LLMs effective psychological assessors? Leveraging adaptive RAG for interpretable mental health screening through psychometric practice

https://github.com/fedelopez77/gyrospd

공식 코드

Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices

https://github.com/feiliu36/eoh

공식 코드

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model

https://github.com/feiwang96/Data-Advisor

공식 코드

Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models

https://github.com/felixchan9527/versagen_official

공식 코드

VersaGen: Unleashing Versatile Visual Control for Text-to-Image Synthesis

https://github.com/fengchen025/PhenoAssistant

공식 코드

PhenoAssistant: A Conversational Multi-Agent AI System for Automated Plant Phenotyping

https://github.com/fenghetan9/llm4seg

공식 코드

Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster

https://github.com/fengranMark/PersonalizedCIR

공식 코드

How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrieval

https://github.com/feradauto/moralcot

공식 코드

When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment

https://github.com/ffzzy840304/masked-pdpp

공식 코드

Masked Diffusion with Task-awareness for Procedure Planning in Instructional Videos

https://github.com/fhshubho/cgs-zsl

공식 코드

ChatGPT-guided Semantics for Zero-shot Learning

https://github.com/fiction-zju/rulegpt

공식 코드

HORAE: A Domain-Agnostic Language for Automated Service Regulation

https://github.com/fiorina1212/attention-buckets

공식 코드

Fortify the Shortest Stave in Attention: Enhancing Context Awareness of Large Language Models for Effective Tool Use

https://github.com/firenze11/finance_lm

공식 코드

Multimodal Gen-AI for Fundamental Investment Research

https://github.com/fireredteam/fireredasr

공식 코드

FireRedASR: Open-Source Industrial-Grade Mandarin Speech Recognition Models from Encoder-Decoder to LLM Integration

https://github.com/fisht0ucher/trident

공식 코드

TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data Synthesis

https://github.com/fjq-tongji/mllm-sul

공식 코드

MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic Scenarios

https://github.com/flagopen/flagembedding

공식 코드

Towards A Generalist Code Embedding Model Based On Massive Data Synthesis

https://github.com/flame-ruc/flame

공식 코드

FLAME: Financial Large-Language Model Assessment and Metrics Evaluation

https://github.com/flavio2018/nesy23

공식 코드

A Hybrid System for Systematic Generalization in Simple Arithmetic Problems

https://github.com/flexflow/flexflow

공식 코드

SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification

https://github.com/flixpar/med-ts-llm

공식 코드

MedTsLLM: Leveraging LLMs for Multimodal Medical Time Series Analysis

https://github.com/floridsleeves/llmdebugger

공식 코드

Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step

https://github.com/floridsleeves/robustapi

공식 코드

Can ChatGPT replace StackOverflow? A Study on Robustness and Reliability of Large Language Model Code Generation

https://github.com/florin-git/Base-vs-Instruct-LLMs-in-RAG-Systems

공식 코드

A Tale of Trust and Accuracy: Base vs. Instruct LLMs in RAG Systems

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