https://github.com/getao/icae
공식 코드In-context Autoencoder for Context Compression in a Large Language Model
Papers with Code 아카이브
Knowledge Graphs
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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/getzep/graphiti
공식 코드Zep: A Temporal Knowledge Graph Architecture for Agent Memory
https://github.com/gewu-lab/sounding-object-segmentation-preference
공식 코드Can Textual Semantics Mitigate Sounding Object Segmentation Preference?
https://github.com/ggcr/tinyemo
공식 코드TinyEmo: Scaling down Emotional Reasoning via Metric Projection
https://github.com/ghrua/ccpr_release
공식 코드https://github.com/ghupppp/memorysharingllm
공식 코드https://github.com/giacoballoccu/explanation-quality-recsys
공식 코드https://github.com/gicheonkang/DAN-VisDial
공식 코드Dual Attention Networks for Visual Reference Resolution in Visual Dialog
https://github.com/gingasan/idge
공식 코드https://github.com/gipplab/MathQA
공식 코드Mining Mathematical Documents for Question Answering via Unsupervised Formula Labeling
https://github.com/gipplab/cl-osa
공식 코드Detecting Cross-Language Plagiarism using Open Knowledge Graphs
https://github.com/git-disl/awesome-llm-game-agent-papers
공식 코드https://github.com/git-disl/gptlens
공식 코드Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives
https://github.com/git-disl/safety-tax
공식 코드Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable
https://github.com/git-disl/vaccine
공식 코드Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attack
https://github.com/githubnext/testpilot
공식 코드An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation
https://github.com/gitter-lab/Assay2Mol
공식 코드Assay2Mol: large language model-based drug design using BioAssay context
https://github.com/gk0wk/xgraphrag
공식 코드XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
https://github.com/gknl/smile
공식 코드SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link Prediction
https://github.com/gkw0010/endochat
공식 코드EndoChat: Grounded Multimodal Large Language Model for Endoscopic Surgery
https://github.com/glaciohound/lerp
공식 코드Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
https://github.com/glowworm-cell/lict
공식 코드Objectively Evaluating the Reliability of Cell Type Annotation Using LLM-Based Strategies
https://github.com/gls0425/linvt
공식 코드LinVT: Empower Your Image-level Large Language Model to Understand Videos
https://github.com/gmaher/llmpc
공식 코드https://github.com/goliaro/specinfer-ae
공식 코드https://github.com/gomate-community/trustrag
공식 코드TrustRAG: An Information Assistant with Retrieval Augmented Generation
https://github.com/google-deepmind/loft
공식 코드Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?
https://github.com/google-research-datasets/rag_conflicts
공식 코드DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs
https://github.com/google-research-datasets/swim-ir
공식 코드Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense Retrieval
https://github.com/google-research/google-research
공식 코드Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models
https://github.com/google-research/google-research/tree/master/table_rag
공식 코드TableRAG: Million-Token Table Understanding with Language Models
https://github.com/google-research/smore
공식 코드SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
https://github.com/govtech-responsibleai/knowornot
공식 코드Know Or Not: a library for evaluating out-of-knowledge base robustness
https://github.com/gowitheflow-1998/rar-b
공식 코드https://github.com/gpt-laboratory/rag-llm-development-guidebook-from-pdfs
공식 코드Developing Retrieval Augmented Generation (RAG) based LLM Systems from PDFs: An Experience Report
https://github.com/gpt4vision/gpt4sgg-llm
공식 코드GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific Narratives
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.