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Hallucination
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zhyang2226/opa-dpo
공식 코드Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key
https://github.com/ziconghe2002/hcl-spark
공식 코드Shakespearean Sparks: The Dance of Hallucination and Creativity in LLMs' Decoding Layers
https://github.com/zippotju/Exposure-Bias-Hallucination-Domain-Shift
공식 코드On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation
https://github.com/ziweiji/Internal_States_Reveal_Hallucination
공식 코드LLM Internal States Reveal Hallucination Risk Faced With a Query
https://github.com/ziweiji/rho
공식 코드RHO ($ρ$): Reducing Hallucination in Open-domain Dialogues with Knowledge Grounding
https://github.com/zju-daily/aistorian
공식 코드AIstorian lets AI be a historian: A KG-powered multi-agent system for accurate biography generation
https://github.com/zjukg/conferenceqa
공식 코드Reliable Academic Conference Question Answering: A Study Based on Large Language Model
https://github.com/zjunlp/Deco
공식 코드MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation
https://github.com/zjunlp/easydetect
공식 코드Unified Hallucination Detection for Multimodal Large Language Models
https://github.com/zjunlp/easyedit
공식 코드WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models
https://github.com/zjunlp/factchd
공식 코드FactCHD: Benchmarking Fact-Conflicting Hallucination Detection
https://github.com/zjunlp/knowagent
공식 코드KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents
https://github.com/zjunlp/knowrl
공식 코드KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality
https://github.com/zli12321/awesome-vlm-papers-and-models
공식 코드https://github.com/zli12321/videohallu
공식 코드VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video Understanding
https://github.com/zli12321/vision-language-models-overview
공식 코드https://github.com/zshsh98/mmd-mp
공식 코드https://github.com/zsquaredz/Herman
공식 코드Reducing Quantity Hallucinations in Abstractive Summarization
https://github.com/zthang/focus
공식 코드Enhancing Uncertainty-Based Hallucination Detection with Stronger Focus
https://github.com/zukangy/kgp-curiousllm
공식 코드CuriousLLM: Elevating Multi-Document QA with Reasoning-Infused Knowledge Graph Prompting
https://github.com/zurichnlp/multipivotnmt
공식 코드Investigating Multi-Pivot Ensembling with Massively Multilingual Machine Translation Models
https://github.com/zurichrain/agi-hallucination
공식 코드https://github.com/zwhe99/MAPS-mt
공식 코드Exploring Human-Like Translation Strategy with Large Language Models
https://github.com/zwhe99/selftraining4unmt
공식 코드Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation
https://github.com/zxd-octopus/ECR
공식 코드https://github.com/zycheiheihei/transferable-visual-prompting
공식 코드Exploring the Transferability of Visual Prompting for Multimodal Large Language Models
https://github.com/zyq0000/gama
공식 코드Think Before You Act: A Two-Stage Framework for Mitigating Gender Bias Towards Vision-Language Tasks
https://gitlab.com/ones-ai/eval-quant-llms
공식 코드https://github.com/Aal-Izz-Well/pulse
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/AlignRM/RLFH
On-Policy Fine-grained Knowledge Feedback for Hallucination Mitigation
https://github.com/AssafSinger94/sigmorphon-2020-inflection
https://github.com/B0B8K1ng/WMNavigation
WMNav: Integrating Vision-Language Models into World Models for Object Goal Navigation
https://github.com/Dragoniss/minspore-phase2-E2FGVI
Towards An End-to-End Framework for Flow-Guided Video Inpainting
https://github.com/EncryptedBinary/Meta_analysis
https://github.com/FKIRSTE/emnlp2024-personalized-meeting-sum
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.