https://github.com/nicoladainese96/code-world-models
공식 코드Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
Papers with Code 아카이브
Knowledge Graph Completion
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- 보존된 평가 기록
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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/nicolas-hbt/versatile-embeddings
공식 코드Schema First! Learn Versatile Knowledge Graph Embeddings by Capturing Semantics with MASCHInE
https://github.com/nicolay-r/semeval2024-task3
공식 코드https://github.com/nicolay-r/thor-ecac
공식 코드https://github.com/nicyscaria/AEQG-MCQ-Distractors-Physics
공식 코드https://github.com/nidryen-zh/privacyannotation
공식 코드Automated Privacy Information Annotation in Large Language Model Interactions
https://github.com/nidryen-zh/questionerawareresponder
공식 코드Personalized LLM for Generating Customized Responses to the Same Query from Different Users
https://github.com/nightdessert/retrieval_head
공식 코드Retrieval Head Mechanistically Explains Long-Context Factuality
https://github.com/nikivanstein/LLaMEA
공식 코드LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics
https://github.com/nikolamilosevic86/verif.ai
공식 코드https://github.com/nil-zhuang/efficientrag-official
공식 코드EfficientRAG: Efficient Retriever for Multi-Hop Question Answering
https://github.com/ninjatech-ai/mple
공식 코드Multi-Programming Language Ensemble for Code Generation in Large Language Model
https://github.com/nishchalprasad/mesc
공식 코드https://github.com/niuchuangnn/vllm_structure
공식 코드https://github.com/niva-knowledge-graph/kgs_and_effect_prediction_2020
공식 코드Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings
https://github.com/nju-pcalab/rag-diffusion
공식 코드Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement
https://github.com/nju-websoft/DSKG
공식 코드DSKG: A Deep Sequential Model for Knowledge Graph Completion
https://github.com/nju-websoft/HyperKA
공식 코드Knowledge Association with Hyperbolic Knowledge Graph Embeddings
https://github.com/nju-websoft/KG2RAG
공식 코드https://github.com/nju-websoft/dift
공식 코드https://github.com/nju-websoft/knowla
공식 코드KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation
https://github.com/nju-websoft/mmrag
공식 코드https://github.com/nju-websoft/mukg
공식 코드$μ\text{KG}$: A Library for Multi-source Knowledge Graph Embeddings and Applications
https://github.com/nju-websoft/tkgc
공식 코드Trustworthy Knowledge Graph Completion Based on Multi-sourced Noisy Data
https://github.com/nju-websoft/unify-ea-sf
공식 코드https://github.com/nk-ruiying/tcompounde
공식 코드Simple but Effective Compound Geometric Operations for Temporal Knowledge Graph Completion
https://github.com/nkai-decision-team/llm-pysc2
공식 코드LLM-PySC2: Starcraft II learning environment for Large Language Models
https://github.com/nkanak/brag-fake-news-campaigns
공식 코드https://github.com/nl2code/attentioncoder
공식 코드Improving Natural Language Capability of Code Large Language Model
https://github.com/nl4opt/nl4opt-competition
공식 코드NL4Opt Competition: Formulating Optimization Problems Based on Their Natural Language Descriptions
https://github.com/nle-ml/mmkb
공식 코드Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
https://github.com/nlp-bin/silc-efsa
공식 코드SILC-EFSA: Self-aware In-context Learning Correction for Entity-level Financial Sentiment Analysis
https://github.com/nlp-rl/ki-ddi
공식 코드Towards Knowledge-Infused Automated Disease Diagnosis Assistant
https://github.com/nlp-uoregon/ullme
공식 코드ULLME: A Unified Framework for Large Language Model Embeddings with Generation-Augmented Learning
https://github.com/nlp-waseda/comet-atomic-ja
공식 코드PHALM: Building a Knowledge Graph from Scratch by Prompting Humans and a Language Model
https://github.com/nlp2ct/hil-mt
공식 코드Human-in-the-loop Machine Translation with Large Language Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.