Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bai-lab/emotionalrag
공식 코드Emotional RAG: Enhancing Role-Playing Agents through Emotional Retrieval
https://github.com/bai-lab/kg-retriever
공식 코드KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models
https://github.com/baichuan-inc/baichuan-audio
공식 코드Baichuan-Audio: A Unified Framework for End-to-End Speech Interaction
https://github.com/baiyuqi/agentic-society
공식 코드Agentic Society: Merging skeleton from real world and texture from Large Language Model
https://github.com/baizhige/eegunity
공식 코드EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Towards Large-Scale EEG Model
https://github.com/baltaci-r/CulturedAgents
공식 코드Persona Inconstancy in Multi-Agent LLM Collaboration: Conformity, Confabulation, and Impersonation
https://github.com/banjiuyufen/Recoverable-Compression
공식 코드Recoverable Compression: A Multimodal Vision Token Recovery Mechanism Guided by Text Information
https://github.com/banjiuyufen/recoverablecompression
공식 코드Recoverable Compression: A Multimodal Vision Token Recovery Mechanism Guided by Text Information
https://github.com/baochi0212/lavy
공식 코드https://github.com/baohaoliao/apiq
공식 코드https://github.com/barshana-banerjee/ParaQA
공식 코드ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversation
https://github.com/bartel-group/matgen_baselines
공식 코드Establishing baselines for generative discovery of inorganic crystals
https://github.com/bashlab/llasa
공식 코드LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone Sensors
https://github.com/batra-mlp-lab/visdial-amt-chat
공식 코드https://github.com/batsresearch/bonito
공식 코드Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation
https://github.com/batsresearch/ex2
공식 코드https://github.com/batsresearch/fudd
공식 코드Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification
https://github.com/batsresearch/nayak-tmlr22-code
공식 코드https://github.com/bayer-group/text-to-sql-epi-ehr-naacl2024
공식 코드https://github.com/baylor-ai/halludetect
공식 코드Detecting Hallucinations in Large Language Model Generation: A Token Probability Approach
https://github.com/bayrameda/MrAP
공식 코드Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation
https://github.com/bbsbz/chemmllm
공식 코드https://github.com/bcdnlp/prd
공식 코드PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations
https://github.com/bdbc-kg-nlp/ngcse
공식 코드https://github.com/bdi-lab/bive
공식 코드Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction
https://github.com/bdi-lab/hynt
공식 코드Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers
https://github.com/bdi-lab/ingram
공식 코드InGram: Inductive Knowledge Graph Embedding via Relation Graphs
https://github.com/bdi-lab/reed
공식 코드PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning
https://github.com/bear96/gabm-epidemic
공식 코드https://github.com/beastyz/llm-verified-retrieval
공식 코드LLatrieval: LLM-Verified Retrieval for Verifiable Generation
https://github.com/beccabai/Data-centric_multimodal_LLM
공식 코드A Survey of Multimodal Large Language Model from A Data-centric Perspective
https://github.com/believewhat/JMLR-Joint-Medical-LLM-and-Retrieval-Training
공식 코드https://github.com/bethxx99/FinTruthQA
공식 코드FinTruthQA: A Benchmark Dataset for Evaluating the Quality of Financial Information Disclosure
https://github.com/betswish/mirage
공식 코드Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation
https://github.com/beyondguo/STA
공식 코드Selective Text Augmentation with Word Roles for Low-Resource Text Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.