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Knowledge Graphs

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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/sam-rag/sam_rag

공식 코드

Self-adaptive Multimodal Retrieval-Augmented Generation

https://github.com/samholt/DiscoPOP

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Discovering Preference Optimization Algorithms with and for Large Language Models

https://github.com/samholt/l2mac

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L2MAC: Large Language Model Automatic Computer for Extensive Code Generation

https://github.com/samleoqh/MSCG-Net

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Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation

https://github.com/samsung/nl-iti

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Non-Linear Inference Time Intervention: Improving LLM Truthfulness

https://github.com/samuelsimko/crl-llm-defense

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Improving Large Language Model Safety with Contrastive Representation Learning

https://github.com/samyateia/bioasq2024

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Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical Tasks

https://github.com/sanchaitahazra/t4text

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To Tell The Truth: Language of Deception and Language Models

https://github.com/sangwu99/simplot

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SIMPLOT: Enhancing Chart Question Answering by Distilling Essentials

https://github.com/sanxing-chen/adv-fake

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Real-time Fake News from Adversarial Feedback

https://github.com/saprmarks/geometry-of-truth

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The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

https://github.com/saptarshi059/cdqa-project

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Towards Efficient Methods in Medical Question Answering using Knowledge Graph Embeddings

https://github.com/sarahmart/hardmath

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HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics

https://github.com/sarashs/fpga_agi

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SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation

https://github.com/sarthak-choudhary/stealthy_attacks_against_rag

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Through the Stealth Lens: Rethinking Attacks and Defenses in RAG

https://github.com/sarus-tech/dp-rag

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RAG with Differential Privacy

https://github.com/sashakolpakov/granni

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Robust affine point matching via quadratic assignment on Grassmannians

https://github.com/sashakolpakov/rag

공식 코드

Robust affine point matching via quadratic assignment on Grassmannians

https://github.com/sashakolpakov/roam

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Robust affine point matching via quadratic assignment on Grassmannians

https://github.com/sashrikap/context-steering

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CoS: Enhancing Personalization and Mitigating Bias with Context Steering

https://github.com/sastpg/covo

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Consistent Paths Lead to Truth: Self-Rewarding Reinforcement Learning for LLM Reasoning

https://github.com/satpreetsingh/racer

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RACER: An LLM-powered Methodology for Scalable Analysis of Semi-structured Mental Health Interviews

https://github.com/satsuki2486441738/fusionaudio

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FusionAudio-1.2M: Towards Fine-grained Audio Captioning with Multimodal Contextual Fusion

https://github.com/saturnmars/derivingstructuredinsightsfromsustainabilityreportsvialargelanguagemodels

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Glitter or Gold? Deriving Structured Insights from Sustainability Reports via Large Language Models

https://github.com/savannahxu79/linkprompt

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$\textit{LinkPrompt}$: Natural and Universal Adversarial Attacks on Prompt-based Language Models

https://github.com/sayands/sgaligner

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SGAligner : 3D Scene Alignment with Scene Graphs

https://github.com/sb-jang/timelychat

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From What to Respond to When to Respond: Timely Response Generation for Open-domain Dialogue Agents

https://github.com/scalable-model-editing/unified-model-editing

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Is Bigger Edit Batch Size Always Better? -- An Empirical Study on Model Editing with Llama-3

https://github.com/scale-lab/politune

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PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models

https://github.com/scalingintelligence/archon

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Archon: An Architecture Search Framework for Inference-Time Techniques

https://github.com/scd158/RMNA

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RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining

https://github.com/schmidt-ju/scene

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SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks

https://github.com/scholarly-wikidata/scholarly-wikidata

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Scholarly Wikidata: Population and Exploration of Conference Data in Wikidata using LLMs

https://github.com/schowdhury671/meerkat

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Meerkat: Audio-Visual Large Language Model for Grounding in Space and Time

https://github.com/sciencenlp-lab/llm-ssc

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Multi-label Sequential Sentence Classification via Large Language Model

https://github.com/scir-hi/huatuo-llama-med-chinese

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Don't Ignore Dual Logic Ability of LLMs while Privatizing: A Data-Intensive Analysis in Medical Domain

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.