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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/0-kaikai-0/sh2

공식 코드

SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully

https://github.com/141forever/diahalu

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DiaHalu: A Dialogue-level Hallucination Evaluation Benchmark for Large Language Models

https://github.com/1zhou-Wang/MemVR

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Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models

https://github.com/2471023025/ralm_survey

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RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

https://github.com/AIML-K/HalluDist

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Pre-trained Language Models Return Distinguishable Probability Distributions to Unfaithfully Hallucinated Texts

https://github.com/ARC-ASU/fine-nwp

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ToW: Thoughts of Words Improve Reasoning in Large Language Models

https://github.com/ATILF-UMR7118/pRAGe

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Retrieve, Generate, Evaluate: A Case Study for Medical Paraphrases Generation with Small Language Models

https://github.com/AikyamLab/hallucinogen

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HALLUCINOGEN: A Benchmark for Evaluating Object Hallucination in Large Visual-Language Models

https://github.com/Applied-Machine-Learning-Lab/AMAR

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Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation

https://github.com/Arlo0o/StereoScene

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Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion

https://github.com/ArrogantL/ChatGPT4CausalReasoning

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Is ChatGPT a Good Causal Reasoner? A Comprehensive Evaluation

https://github.com/BT-C/HIO

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Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization

https://github.com/CASOS-IDeaS-CMU/SegSub

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SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Models

https://github.com/CYandYue/Dentist

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A Unified Hallucination Mitigation Framework for Large Vision-Language Models

https://github.com/CaoYuanpu/BiPO

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Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization

https://github.com/Cold-Winter/BachGAN

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BachGAN: High-Resolution Image Synthesis from Salient Object Layout

https://github.com/DISL-Lab/FineSurE

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FineSurE: Fine-grained Summarization Evaluation using LLMs

https://github.com/DoubtedSteam/MM-GCoT

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Grounded Chain-of-Thought for Multimodal Large Language Models

https://github.com/EvoNexusX/Graph-Retrieval-Augmented-Trustworthiness-Reasoning

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GRATR: Zero-Shot Evidence Graph Retrieval-Augmented Trustworthiness Reasoning

https://github.com/F-Yuan303/HELPD

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HELPD: Mitigating Hallucination of LVLMs by Hierarchical Feedback Learning with Vision-enhanced Penalty Decoding

https://github.com/FBzzh/CACDD

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A Claim Decomposition Benchmark for Long-form Answer Verification

https://github.com/FuxiaoLiu/LRV-Instruction

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Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

https://github.com/Georgetown-IR-Lab/GAuGE

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Genetic Approach to Mitigate Hallucination in Generative IR

https://github.com/HDCVLab/EDFace-Celeb-1M

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EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset

https://github.com/Helsinki-NLP/mu-shroom

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SemEval-2025 Task 3: Mu-SHROOM, the Multilingual Shared Task on Hallucinations and Related Observable Overgeneration Mistakes

https://github.com/IAAR-Shanghai/UHGEval

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UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation

https://github.com/InternLM/InternLM-XComposer/tree/main/projects/DualFocus

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DualFocus: Integrating Macro and Micro Perspectives in Multi-modal Large Language Models

https://github.com/JackChen-seu/Reefknot

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Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models

https://github.com/JalaliLabUCLA/Jalali-Lab-Implementation-of-RAISR

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Brain MRI Image Super Resolution using Phase Stretch Transform and Transfer Learning

https://github.com/KRLabsOrg/LettuceDetect

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LettuceDetect: A Hallucination Detection Framework for RAG Applications

https://github.com/KaiWU5/NoiseBoost

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NoiseBoost: Alleviating Hallucination with Noise Perturbation for Multimodal Large Language Models

https://github.com/KamitaniLab/GOD_stimuli_annotations

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Spurious reconstruction from brain activity

https://github.com/KomeijiForce/LinCorr

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Linear Correlation in LM's Compositional Generalization and Hallucination

https://github.com/LUMIA-Group/SH2

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SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully

https://github.com/LucusFigoGao/AIGCs_Confuse_AI_Too

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AIGCs Confuse AI Too: Investigating and Explaining Synthetic Image-induced Hallucinations in Large Vision-Language Models

https://github.com/LzVv123456/VISTA

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The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models via Visual Information Steering

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