https://github.com/zou-group/avatar
공식 코드AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning
Papers with Code 아카이브
Inductive knowledge graph completion
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zou-yawen/dataset-distillation-via-vision-language-category-prototype
공식 코드https://github.com/zrporz/4DLangSplat
공식 코드4D LangSplat: 4D Language Gaussian Splatting via Multimodal Large Language Models
https://github.com/zrrskywalker/mavis
공식 코드MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine
https://github.com/zukangy/kgp-curiousllm
공식 코드CuriousLLM: Elevating Multi-Document QA with Reasoning-Infused Knowledge Graph Prompting
https://github.com/zwt233/Grain
공식 코드Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization
https://github.com/zxccade/shine
공식 코드SHINE: Saliency-aware HIerarchical NEgative Ranking for Compositional Temporal Grounding
https://github.com/zxd-octopus/vricr
공식 코드Variational Reasoning over Incomplete Knowledge Graphs for Conversational Recommendation
https://github.com/zxlzr/legalpp
공식 코드https://github.com/zychen423/KE-VIST
공식 코드https://github.com/zyf0619sjtu/DreamLIP
공식 코드https://github.com/zyloveslego/LLMCheck
공식 코드https://github.com/zyzhangustc/mellm
공식 코드MELLM: Exploring LLM-Powered Micro-Expression Understanding Enhanced by Subtle Motion Perception
https://github.com/zyzisastudyreallyhardguy/llm4sd
공식 코드Large Language Models for Scientific Synthesis, Inference and Explanation
https://github.com/zz1358m/mcts-ahd-master
공식 코드Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
https://github.com/zzoliman/covid-vaccine-misinfo-mic
공식 코드https://gitlab.com/boshko.koloski/codename_fn_b
공식 코드Knowledge Graph informed Fake News Classification via Heterogeneous Representation Ensembles
https://gitlab.com/chen00217/bert_subsumption
공식 코드Contextual Semantic Embeddings for Ontology Subsumption Prediction
https://gitlab.com/patryk.preisner/mkga
공식 코드Universal Preprocessing Operators for Embedding Knowledge Graphs with Literals
https://gitlab.com/sphelps/llm-cooperation
공식 코드https://gitlab.com/wxwilcke/mrgcn
공식 코드End-to-End Entity Classification on Multimodal Knowledge Graphs
https://gitlab.irlab.org/irlab/cabuxa
공식 코드Conversations in Galician: a Large Language Model for an Underrepresented Language
https://huggingface.co/aminhaeri/risk-embed
공식 코드Generative AI Enhanced Financial Risk Management Information Retrieval
https://huggingface.co/emilgoh/mistral-verilog
공식 코드From English to ASIC: Hardware Implementation with Large Language Model
https://huggingface.co/jslin09/bloom-560m-finetuned-fraud
공식 코드Legal Documents Drafting with Fine-Tuned Pre-Trained Large Language Model
https://huggingface.co/mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B
공식 코드TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools
https://huggingface.co/mims-harvard/TxAgent-T1-Llama-3.1-8B
공식 코드TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools
https://us-south.git.cloud.ibm.com/anu-kg/legal-kg
공식 코드https://worksheets.codalab.org/worksheets/0xc757f29f5c794e5eb7bfa8ca9c945573
공식 코드Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings
https://worksheets.codalab.org/worksheets/0xf215deb05edf44a2ac353c711f52a25f
공식 코드QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://worksheets.codalab.org/worksheets/0xfcace41fdeec45f3bc6ddf31107b829f
공식 코드https://zenodo.org/record/10500594
공식 코드https://zenodo.org/record/7916716
공식 코드Text2KGBench: A Benchmark for Ontology-Driven Knowledge Graph Generation from Text
https://github.com/01-ai/yi
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
https://github.com/1171-jpg/brainteaser
BRAINTEASER: Lateral Thinking Puzzles for Large Language Models
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/advanced_east
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.