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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/FuxiaoLiu/VisualNews-Repository

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

https://github.com/Guang000/Awesome-Dataset-Distillation

Dataset Distillation via Factorization

https://github.com/HilaManor/Generative-deep-features

Projected Distribution Loss for Image Enhancement

https://github.com/IDEA-FinAI/Simple-HHEA

Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph

https://github.com/JT-Sun/Filtering-WoRA

VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty Estimation

https://github.com/KandariSrinivas/Adversarial-Feature-Hallucination-Networks-for-Few-Shot-Learning

Adversarial Feature Hallucination Networks for Few-Shot Learning

https://github.com/LisaAnne/Hallucination

Object Hallucination in Image Captioning

https://github.com/MS-P3/code6/tree/main/rag

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

https://github.com/Martion-z/Paddle-PULSE

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

https://github.com/Martion-z/pytorch-Pulse

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

https://github.com/Mind23-2/MindCode-174

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

https://github.com/MindCode-4/code-4/tree/main/qwen2_vl

RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models

https://github.com/MindCode-4/code-8/tree/main/Projected-Distribution

Projected Distribution Loss for Image Enhancement

https://github.com/MindSpore-paper-code-2/code3/tree/main/ViG

VIGC: Visual Instruction Generation and Correction

https://github.com/MindSpore-scientific-2/code-14/tree/main/llava

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

https://github.com/MindSpore-scientific/code-5/tree/main/Projected-Distribution

Projected Distribution Loss for Image Enhancement

https://github.com/OpenGVLab/TimeSuite

TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning

https://github.com/PKU-YuanGroup/Video-LLaVA

MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

https://github.com/ParitoshParmar/HalluciNet--PyTorch

HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN

https://github.com/RUCAIBox/Slow_Thinking_with_LLMs

Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking

https://github.com/RylanSchaeffer/prismatic-vlms

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models

https://github.com/Sapphire-356/TASC

The Mirage of Performance Gains: Why Contrastive Decoding Fails to Address Multimodal Hallucination

https://github.com/Slayerxxx/E-RAISR

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

https://github.com/Spracks/PackageHallucination

We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs

https://github.com/Sreyan88/GAMA

Understanding Sounds, Missing the Questions: The Challenge of Object Hallucination in Large Audio-Language Models

https://github.com/SteveTANTAN/PoG

Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning

https://github.com/YashNita/Separate-Object-Sounds-by-Watching-Unlabeled-Video-PyTorch-

Im2Flow: Motion Hallucination from Static Images for Action Recognition

https://github.com/ZoieMo/Multi-task

Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination

https://github.com/agrzheng/GRADA

PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models

https://github.com/ai4eic/eic-rag-project

Retrieval-Augmented Generation for Large Language Models: A Survey

https://github.com/ajd12342/inflection-pytorch

Pushing the Limits of Low-Resource Morphological Inflection

https://github.com/amazon-science/bschecker-for-fine-grained-hallucination-detection

RefChecker: Reference-based Fine-grained Hallucination Checker and Benchmark for Large Language Models

https://github.com/amazon-science/llm-asymptotic-decoding

REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation via Asymptotic Entropy

https://github.com/andy9705/SumGD

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding

https://github.com/aoidragon/pope

Evaluating Object Hallucination in Large Vision-Language Models

https://github.com/b5071/pulse-rev

PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

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