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Large Language Model
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gatenlp/h3prompt
공식 코드https://github.com/gautierdag/plancraft
공식 코드Plancraft: an evaluation dataset for planning with LLM agents
https://github.com/gavin001201/cof
공식 코드CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models
https://github.com/gblackout/TILR
공식 코드https://github.com/gchochla/vault
공식 코드VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media
https://github.com/gcyzsl/o3-llm-unlearning
공식 코드https://github.com/ge-semtk/semtk
공식 코드SemTK: An Ontology-first, Open Source Semantic Toolkit for Managing and Querying Knowledge Graphs
https://github.com/geekan/metagpt
공식 코드https://github.com/geekjuruo/beer2
공식 코드Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity Linking
https://github.com/gen-verse/scoreflow
공식 코드ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization
https://github.com/generative-social-choice/chatbot_personalization_data
공식 코드https://github.com/genetasefa/raild
공식 코드RAILD: Towards Leveraging Relation Features for Inductive Link Prediction In Knowledge Graphs
https://github.com/gengchenmai/Attention_GraphQA
공식 코드Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs
https://github.com/geobrain-ai/geogalactica
공식 코드GeoGalactica: A Scientific Large Language Model in Geoscience
https://github.com/geofila/Semantic-Counterfactuals
공식 코드Choose your Data Wisely: A Framework for Semantic Counterfactuals
https://github.com/georgiarg/autofashion
공식 코드Automatic Generation of Fashion Images using Prompting in Generative Machine Learning Models
https://github.com/geox-lab/allspark
공식 코드https://github.com/geox-lab/hook
공식 코드Homogeneous Tokenizer Matters: Homogeneous Visual Tokenizer for Remote Sensing Image Understanding
https://github.com/geox-lab/rs-gpt4v
공식 코드RS-GPT4V: A Unified Multimodal Instruction-Following Dataset for Remote Sensing Image Understanding
https://github.com/getao/icae
공식 코드In-context Autoencoder for Context Compression in a Large Language Model
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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.