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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/mrgiovanni/radgpt

공식 코드

RadGPT: Constructing 3D Image-Text Tumor Datasets

https://github.com/mrzilinxiao/autover

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Grounding Language Models for Visual Entity Recognition

https://github.com/msorkhpar/wiki-entity-summarization

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Wiki Entity Summarization Benchmark

https://github.com/mstubbemann/Orometric-Methods-in-Bounded-Metric-Data

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Orometric Methods in Bounded Metric Data

https://github.com/mstubbemann/lg4av

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LG4AV: Combining Language Models and Graph Neural Networks for Author Verification

https://github.com/mtkresearch/rad-bench

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RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues

https://github.com/mu-data-science/gaf

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A Scalable Tool For Analyzing Genomic Variants Of Humans Using Knowledge Graphs and Machine Learning

https://github.com/muellerlab/synthesizing_interpretable_control_policies

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Synthesizing Interpretable Control Policies through Large Language Model Guided Search

https://github.com/muguruzawang/kgsum

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Multi-Document Scientific Summarization from a Knowledge Graph-Centric View

https://github.com/muktac5/ciir-liverag

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CIIR@LiveRAG 2025: Optimizing Multi-Agent Retrieval Augmented Generation through Self-Training

https://github.com/multimodal-art-projection/map-neo

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MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series

https://github.com/mungomeng/survival-xsurv

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Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer

https://github.com/murongyue/llm_mot_cascade

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Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning

https://github.com/mushfiqur11/simpledc-dataset

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Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement Learning

https://github.com/mustafakarabag/llmchameleon

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Do LLMs Strategically Reveal, Conceal, and Infer Information? A Theoretical and Empirical Analysis in The Chameleon Game

https://github.com/mutiann/ccc

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On the Role of Conceptualization in Commonsense Knowledge Graph Construction

https://github.com/mxpoliakov/multi-meta-rag

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Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata

https://github.com/my-ai-university/finite-element-method

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AI-University: An LLM-based platform for instructional alignment to scientific classrooms

https://github.com/myazann/ap-bots

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Improving RAG for Personalization with Author Features and Contrastive Examples

https://github.com/myeon9h/planrag

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PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers

https://github.com/mysong7nlper/chatgpt_as_keyphrase_extractor

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Large Language Models as Zero-Shot Keyphrase Extractors: A Preliminary Empirical Study

https://github.com/n28div/llm-disjointness

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Enriching Ontologies with Disjointness Axioms using Large Language Models

https://github.com/n4feng/ResponseQualityAssessment

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Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality

https://github.com/nadavlab/CPLLM

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CPLLM: Clinical Prediction with Large Language Models

https://github.com/naist-nlp/CC_RAG

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Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domain

https://github.com/namin/llm-verified-with-monte-carlo-tree-search

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VerMCTS: Synthesizing Multi-Step Programs using a Verifier, a Large Language Model, and Tree Search

https://github.com/nan-huo/micro-act

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Micro-Act: Mitigate Knowledge Conflict in Question Answering via Actionable Self-Reasoning

https://github.com/narabzad/genir-evaluation

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A Comparison of Methods for Evaluating Generative IR

https://github.com/narabzad/prompt-sensitivity-relevance-judgements

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A Human-AI Comparative Analysis of Prompt Sensitivity in LLM-Based Relevance Judgment

https://github.com/nasrinkalanat/skg-sym

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Symbolic image detection using scene and knowledge graphs

https://github.com/national-center-for-ai-saudi-arabia/lm-evaluation-harness

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When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards

https://github.com/naumannaeem/bea_2025

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NeuralNexus at BEA 2025 Shared Task: Retrieval-Augmented Prompting for Mistake Identification in AI Tutors

https://github.com/naver-ai/korean-safety-benchmarks

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KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Application

https://github.com/naver-ai/tablevqabench

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TableVQA-Bench: A Visual Question Answering Benchmark on Multiple Table Domains

https://github.com/naver-intel-co-lab/gaudi-lavcap

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LAVCap: LLM-based Audio-Visual Captioning using Optimal Transport

https://github.com/naver/bergen

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BERGEN: A Benchmarking Library for Retrieval-Augmented Generation

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