https://github.com/riedlerm/multimodal_rag_for_industry
공식 코드Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial Applications
Papers with Code 아카이브
Knowledge Graph Completion
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 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: $(h, r, ?)$.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/riflezhang/llava-hound-dpo
공식 코드Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward
https://github.com/rightbank/narrative-cartography-ontology
공식 코드https://github.com/rikdz/GraphWriter
공식 코드Text Generation from Knowledge Graphs with Graph Transformers
https://github.com/rikeilong/bay-cat
공식 코드CAT: Enhancing Multimodal Large Language Model to Answer Questions in Dynamic Audio-Visual Scenarios
https://github.com/riken-dko/generation_sparql
공식 코드https://github.com/rintaro-ando-tech/n2m-rsi-demo
공식 코드When Your Own Output Becomes Your Training Data: Noise-to-Meaning Loops and a Formal RSI Trigger
https://github.com/ritaranx/clingen
공식 코드https://github.com/ritaranx/collab-rag
공식 코드https://github.com/ritatsousa/expressionKGplus
공식 코드Multi-dataset and Transfer Learning Using Gene Expression Knowledge Graphs
https://github.com/ritatsousa/expressionkg
공식 코드https://github.com/riyazahuja/ImProver
공식 코드https://github.com/rizquuula/QASiNa
공식 코드QASiNa: Religious Domain Question Answering using Sirah Nabawiyah
https://github.com/rkzheng99/villa
공식 코드ViLLa: Video Reasoning Segmentation with Large Language Model
https://github.com/rlhflow/online-rlhf
공식 코드https://github.com/rloganiv/kglm-model
공식 코드Barack's Wife Hillary: Using Knowledge-Graphs for Fact-Aware Language Modeling
https://github.com/rlqja1107/NL-VSGG
공식 코드Weakly Supervised Video Scene Graph Generation via Natural Language Supervision
https://github.com/rlqja1107/torch-LLM4SGG
공식 코드LLM4SGG: Large Language Models for Weakly Supervised Scene Graph Generation
https://github.com/rmanluo/np-fkgc
공식 코드Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
https://github.com/rmit-ir/GRAG-LiveRAG
공식 코드https://github.com/rmit-ir/walert
공식 코드https://github.com/rmldj/memory-llm-paper
공식 코드https://github.com/rmovva/llm-publication-patterns-public
공식 코드Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers
https://github.com/roaminsight/roamresearch
공식 코드Retrofitting Distributional Embeddings to Knowledge Graphs with Functional Relations
https://github.com/robert1003/ash-prompting
공식 코드Hierarchical Prompting Assists Large Language Model on Web Navigation
https://github.com/robertlakatos/ragvsfn
공식 코드https://github.com/robertvacareanu/llm4regression
공식 코드https://github.com/robinyjpark/autolabelclassifier
공식 코드Automated Spinal MRI Labelling from Reports Using a Large Language Model
https://github.com/rohangiriraj/CausalKG
공식 코드https://github.com/rongyaofang/got
공식 코드https://github.com/ronit-singhal/evidence-backed-fact-checking-using-rag-and-few-shot-in-context-learning-with-llms
공식 코드Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMs
https://github.com/roshnigiyer/dgs
공식 코드Dual-Geometric Space Embedding Model for Two-View Knowledge Graphs
https://github.com/royahe/acone
공식 코드Generating $SROI^-$ Ontologies via Knowledge Graph Query Embedding Learning
https://github.com/royweiss1/GPT_Keylogger
공식 코드What Was Your Prompt? A Remote Keylogging Attack on AI Assistants
https://github.com/rqwang/floodgpt_prototype
공식 코드https://github.com/rshaojimmy/jiutian
공식 코드LION : Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.