Papers with Code 아카이브
Knowledge Graph Completion
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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: $(h, r, ?)$.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List
공식 코드https://github.com/wangyh-bupt/dairstega
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https://github.com/wangyu0627/irllrec
공식 코드Intent Representation Learning with Large Language Model for Recommendation
https://github.com/wangzc1233/Prot2Chat
공식 코드Prot2Chat: Protein LLM with Early-Fusion of Text, Sequence and Structure
https://github.com/waterhorse1/llm_tree_search
공식 코드Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training
https://github.com/wazenmai/hc-smoe
공식 코드Retraining-Free Merging of Sparse MoE via Hierarchical Clustering
https://github.com/wbbeyourself/scm4llms
공식 코드Enhancing Large Language Model with Self-Controlled Memory Framework
https://github.com/weaidb/awesome-data-llm
공식 코드https://github.com/weaidb/awsome-data-llm
공식 코드https://github.com/weaidb/cracksql
공식 코드CrackSQL: A Hybrid SQL Dialect Translation System Powered by Large Language Models
https://github.com/webeng/llm_knowledge_gap_finder
공식 코드Harnessing Retrieval-Augmented Generation (RAG) for Uncovering Knowledge Gaps
https://github.com/webis-de/ecir-25
공식 코드Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-Ranking
https://github.com/webis-de/msmarco-llm-distillation
공식 코드Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-Ranking
https://github.com/webis-de/scolia25-xsum
공식 코드Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature Summarization
https://github.com/webis-de/sigir25-rag-crowdsourcing
공식 코드https://github.com/wecoai/aideml
공식 코드RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts
https://github.com/weichenzh/open3dvqa
공식 코드https://github.com/weihaox/UMBRAE
공식 코드https://github.com/weihuanglin/inf-llava
공식 코드INF-LLaVA: Dual-perspective Perception for High-Resolution Multimodal Large Language Model
https://github.com/weiiguo/wireless-agent
공식 코드WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
https://github.com/weijiawu/paradiffusion
공식 코드Paragraph-to-Image Generation with Information-Enriched Diffusion Model
https://github.com/weikang-wang/NationalityBiasOfChatGPT
공식 코드Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPT
https://github.com/weiminxiong/ipr
공식 코드Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement
https://github.com/weimo3221/FUZZ-CODER
공식 코드https://github.com/weitaikang/robin3d
공식 코드Robin3D: Improving 3D Large Language Model via Robust Instruction Tuning
https://github.com/weiyanbin1999/kicgpt
공식 코드KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion
https://github.com/weiyifan1023/senator
공식 코드Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs
https://github.com/weiyumou/KCluster
공식 코드KCluster: An LLM-based Clustering Approach to Knowledge Component Discovery
https://github.com/weizhepei/instructrag
공식 코드InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
https://github.com/wellecks/llmstep
공식 코드https://github.com/wenboown/generative-ai-for-semiconductor-physical-design
공식 코드Enhancing Reasoning to Adapt Large Language Models for Domain-Specific Applications
https://github.com/wendy-xiao/chatgpt_editing_summ
공식 코드Personalized Abstractive Summarization by Tri-agent Generation Pipeline
https://github.com/wenkehuang/awesome-mllm-tuning
공식 코드Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model
https://github.com/wentao-xu/kge-cl
공식 코드KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings
https://github.com/wentaotan/mllm4text-reid
공식 코드Harnessing the Power of MLLMs for Transferable Text-to-Image Person ReID
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