https://github.com/snap-stanford/biodiscoveryagent
공식 코드BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
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/snoels/fingeit
공식 코드https://github.com/snowflakedb/ArcticTraining
공식 코드Arctic Long Sequence Training: Scalable And Efficient Training For Multi-Million Token Sequences
https://github.com/snowflakedb/arcticinference
공식 코드SuffixDecoding: Extreme Speculative Decoding for Emerging AI Applications
https://github.com/snowteam2023/medrag
공식 코드https://github.com/sntcristian/and-kge
공식 코드A Knowledge Graph Embeddings based Approach for Author Name Disambiguation using Literals
https://github.com/snu-mllab/guidedquant
공식 코드GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
https://github.com/social-futures-lab/muse
공식 코드Correcting misinformation on social media with a large language model
https://github.com/socialfoundations/benchmark-prediction
공식 코드https://github.com/sola-st/RepairAgent
공식 코드RepairAgent: An Autonomous, LLM-Based Agent for Program Repair
https://github.com/sola-st/executionagent
공식 코드You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary Projects
https://github.com/soledad921/ATISE
공식 코드Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition
https://github.com/solidlabnetwork/awesome-distributed-LLM
공식 코드https://github.com/som-shahlab/clinfo.ai
공식 코드https://github.com/somsubhra04/aisome_2023
공식 코드Decoding Concerns: Multi-label Classification of Vaccine Sentiments in Social Media
https://github.com/sonalkum/compun
공식 코드https://github.com/song-wx/sift
공식 코드Sparse is Enough in Fine-tuning Pre-trained Large Language Models
https://github.com/sonnygeorge/oedd
공식 코드https://github.com/sotopia-lab/sotopia-pi
공식 코드SOTOPIA-$π$: Interactive Learning of Socially Intelligent Language Agents
https://github.com/souradipp76/ReadMeReady
공식 코드Free and Customizable Code Documentation with LLMs: A Fine-Tuning Approach
https://github.com/spackows/icaai-2024_rag-cd
공식 코드https://github.com/spark-damian/s-ui
공식 코드Leveraging Multimodal LLM for Inspirational User Interface Search
https://github.com/sparksjoe/prism
공식 코드Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs
https://github.com/spcl/mrag
공식 코드https://github.com/spearsheep/APT-Architectural-Planning-LLM-Agent
공식 코드https://github.com/sperfu/eyedoc
공식 코드https://github.com/spfrommer/cse-ranking-manipulation
공식 코드https://github.com/spfrommer/ragdoll-data-pipeline
공식 코드https://github.com/spfrommer/ranking_manipulation
공식 코드https://github.com/spfrommer/ranking_manipulation_data_pipeline
공식 코드https://github.com/spotify-research/tot
공식 코드https://github.com/springcty/rag-fragility-to-linguistic-variation
공식 코드https://github.com/sprocketlab/alchemist
공식 코드The ALCHEmist: Automated Labeling 500x CHEaper Than LLM Data Annotators
https://github.com/spursgozmy/table-llava
공식 코드https://github.com/srgrace/contextual-compression
공식 코드Contextual Compression in Retrieval-Augmented Generation for Large Language Models: A Survey
https://github.com/sshaghayeghs/llama-vs-chatgpt
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.