https://github.com/pku-dair/hetu-galvatron
FlexSP: Accelerating Large Language Model Training via Flexible Sequence Parallelism
Papers with Code 아카이브
Knowledge Graphs
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 4
- 보존된 평가 기록
- 19
A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pku-yuangroup/languagebind
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/pku-yuangroup/video-bench
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/pminervini/kgreasoning
https://github.com/pomonam/kronfluence
Studying Large Language Model Generalization with Influence Functions
https://github.com/prannaykaul/mm-ovod
Multi-Modal Classifiers for Open-Vocabulary Object Detection
https://github.com/princeton-nlp/unintentional-unalignment
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors
https://github.com/prithivirajdamodaran/flashrank
COS-Mix: Cosine Similarity and Distance Fusion for Improved Information Retrieval
https://github.com/protllm/protllm
ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training
https://github.com/purduedigitaltwin/talk2drive
Personalized Autonomous Driving with Large Language Models: Field Experiments
https://github.com/pwc-1/Paper-5/tree/main/mistral
https://github.com/pwc-1/Paper-9/tree/main/2/minigpt4
https://github.com/pwc-1/Paper-9/tree/main/2/mobilebert
PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERT
https://github.com/pwc-1/Paper-9/tree/main/6/CAJ/src/models
Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning
https://github.com/pwc-1/Paper-9/tree/main/jamba
https://github.com/pwc-1/Paper-9/tree/main/llama
LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model
https://github.com/pyg-team/pytorch_geometric/blob/master/torch_geometric/nn/kge/rotate.py
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
https://github.com/qingyun-wu/autogen-eval
Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference
https://github.com/qirui-chen/MultiHop-EgoQA
https://github.com/qiujihao19/artemis
GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest
https://github.com/qizekun/ReCon
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
https://github.com/rabiulcste/vqazero
Kosmos-2: Grounding Multimodal Large Language Models to the World
https://github.com/rachtibat/lrp-explains-transformers
https://github.com/rachtibat/lrp-for-transformers
https://github.com/rahmanidashti/acqsurvey
https://github.com/raincleared-song/sparse_gpu_operator
PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU
https://github.com/raphaelsty/mkb
Inductive Entity Representations from Text via Link Prediction
https://github.com/rasmith/vllm
Efficient Memory Management for Large Language Model Serving with PagedAttention
https://github.com/reczoo/FuxiCTR/tree/main/model_zoo/WuKong
Wukong: Towards a Scaling Law for Large-Scale Recommendation
https://github.com/relic-yuexi/agentcourt
DeliLaw: A Chinese Legal Counselling System Based on a Large Language Model
https://github.com/renmengjie7/aisimutoolkit
https://github.com/rle-foundation/hsuanwu
RLLTE: Long-Term Evolution Project of Reinforcement Learning
https://github.com/robotics-4-all/ISSEL-Announcements
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/rothamsted/rdf2pg
https://github.com/rucaibox/safe
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/ruckbreasoning/tablellm
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.