https://github.com/ethz-spylab/ctf-satml24-data-analysis
공식 코드Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
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/eustema-s-p-a/scarf
공식 코드https://github.com/event-ahu/eventstr
공식 코드EventSTR: A Benchmark Dataset and Baselines for Event Stream based Scene Text Recognition
https://github.com/event-ahu/medical_image_analysis
공식 코드R2GenCSR: Retrieving Context Samples for Large Language Model based X-ray Medical Report Generation
https://github.com/event-ahu/openpar
공식 코드https://github.com/event-ahu/vfm-det
공식 코드VFM-Det: Towards High-Performance Vehicle Detection via Large Foundation Models
https://github.com/everm0re/erarag-official
공식 코드EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora
https://github.com/evkg/evkg
공식 코드https://github.com/evolvinglmms-lab/multimodal-search-r1
공식 코드https://github.com/ewendawi/llamea-bo
공식 코드https://github.com/ewok-core/ewok
공식 코드https://github.com/ewok-core/ewok-paper
공식 코드https://github.com/exlaw/dlma
공식 코드Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation
https://github.com/expertailab/textual-entailment-for-effective-triple-validation-in-object-prediction
공식 코드Textual Entailment for Effective Triple Validation in Object Prediction
https://github.com/explainableml/zeraucap
공식 코드Zero-shot audio captioning with audio-language model guidance and audio context keywords
https://github.com/explainableml/zs-a2t
공식 코드Zero-shot Translation of Attention Patterns in VQA Models to Natural Language
https://github.com/exploration-lab/iitk-semeval-2024-task-2-clinical-nli
공식 코드https://github.com/ezelikman/parsel
공식 코드Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions
https://github.com/f4biian/hallurag
공식 코드https://github.com/facebookresearch/GraphLog
공식 코드https://github.com/facebookresearch/crag
공식 코드https://github.com/facebookresearch/dual-system-for-visual-language-reasoning
공식 코드DOMINO: A Dual-System for Multi-step Visual Language Reasoning
https://github.com/facebookresearch/fastText
공식 코드https://github.com/facebookresearch/head-to-tail
공식 코드https://github.com/facebookresearch/motif
공식 코드Motif: Intrinsic Motivation from Artificial Intelligence Feedback
https://github.com/facebookresearch/oni
공식 코드Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback
https://github.com/facebookresearch/reasonir
공식 코드https://github.com/facebookresearch/ssl-relation-prediction
공식 코드https://github.com/facebookresearch/sweet_rl
공식 코드SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks
https://github.com/facebookresearch/vjepa2
공식 코드V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
https://github.com/facebookresearch/zero
공식 코드https://github.com/faisalqarah/saudibert
공식 코드SaudiBERT: A Large Language Model Pretrained on Saudi Dialect Corpora
https://github.com/fangguo1/mcranker
공식 코드MCRanker: Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers
https://github.com/fangshiyuu/codrivingllm
공식 코드https://github.com/fanhaoxiang1/litlinker
공식 코드https://github.com/fanourakis/experimental-review-ea
공식 코드Knowledge Graph Embedding Methods for Entity Alignment: An Experimental Review
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.