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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/vyraun/hallucinations

공식 코드

The Curious Case of Hallucinations in Neural Machine Translation

https://github.com/waitxian/hicd

공식 코드

HICD: Hallucination-Inducing via Attention Dispersion for Contrastive Decoding to Mitigate Hallucinations in Large Language Models

https://github.com/waldenruc/ufo

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UFO: a Unified and Flexible Framework for Evaluating Factuality of Large Language Models

https://github.com/wang-ml-lab/multimodal-needle-in-a-haystack

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Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models

https://github.com/wangclnlp/vision-llm-alignment

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RoVRM: A Robust Visual Reward Model Optimized via Auxiliary Textual Preference Data

https://github.com/wangfen01/chartinsighter

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ChartInsighter: An Approach for Mitigating Hallucination in Time-series Chart Summary Generation with A Benchmark Dataset

https://github.com/weijia-xu/hallucinations-in-nmt

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Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection

https://github.com/wenhuang2000/vhtest

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Visual Hallucinations of Multi-modal Large Language Models

https://github.com/wenliangdai/vlp-object-hallucination

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Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-training

https://github.com/westlake-autolab/biokgbench.github.io

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BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science

https://github.com/whongzhong/MMHalSnowball

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Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models

https://github.com/wiselnn570/videorope

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VideoRoPE: What Makes for Good Video Rotary Position Embedding?

https://github.com/wj210/Self-Training-LLM

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Self-training Large Language Models through Knowledge Detection

https://github.com/wjn1996/instructgraph

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InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment

https://github.com/wu0409/antidote

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Antidote: A Unified Framework for Mitigating LVLM Hallucinations in Counterfactual Presupposition and Object Perception

https://github.com/wujunjie1998/tri-he

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Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models

https://github.com/wuxiyang1996/AutoHallusion

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AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

https://github.com/wyl-willing/MindMap

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MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models

https://github.com/x-plug/mplug-halowl

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Hallucination Augmented Contrastive Learning for Multimodal Large Language Model

https://github.com/xiami2019/halluqa

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Evaluating Hallucinations in Chinese Large Language Models

https://github.com/xiaoxinhe/g-retriever

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G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

https://github.com/xiezikai/reflexiveprompting

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Order Matters in Hallucination: Reasoning Order as Benchmark and Reflexive Prompting for Large-Language-Models

https://github.com/xing0047/cca-llava

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Mitigating Object Hallucination via Concentric Causal Attention

https://github.com/xlchen0205/mod

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Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models

https://github.com/xuekai-zhu/pad

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PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning

https://github.com/xunannancy/decoprompt

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DecoPrompt : Decoding Prompts Reduces Hallucinations when Large Language Models Meet False Premises

https://github.com/xxtars/emotionhallucer

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EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models

https://github.com/y0mingzhang/prompt-extraction

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Effective Prompt Extraction from Language Models

https://github.com/yakir-yehuda/interrogatellm

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InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers

https://github.com/yale-nlp/fine-grained-lt

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On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization

https://github.com/yangyi-chen/prior

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Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training

https://github.com/yanxuzhu/kg-fpq

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KG-FPQ: Evaluating Factuality Hallucination in LLMs with Knowledge Graph-based False Premise Questions

https://github.com/yaochenzhu/llm4rec

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Collaborative Large Language Model for Recommender Systems

https://github.com/yaooxu/gog

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Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question Answering

https://github.com/ydk122024/cdt

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Improving Factuality in Large Language Models via Decoding-Time Hallucinatory and Truthful Comparators

https://github.com/yeates/dmt

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Deficiency-Aware Masked Transformer for Video Inpainting

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