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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/MAGICS-LAB/Chain-of-Actions

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Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models

https://github.com/MCG-NKU/E2FGVI

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Towards An End-to-End Framework for Flow-Guided Video Inpainting

https://github.com/MJ-Bench/MJ-Bench

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MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?

https://github.com/MahjabinNahar/CatchMeIfYouSearch

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Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations

https://github.com/MartinBoeckling/KGRag

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Walk&Retrieve: Simple Yet Effective Zero-shot Retrieval-Augmented Generation via Knowledge Graph Walks

https://github.com/Mlair77/nmt_adequacy

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Prevent the Language Model from being Overconfident in Neural Machine Translation

https://github.com/MorningStarOvO/ProAPO

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ProAPO: Progressively Automatic Prompt Optimization for Visual Classification

https://github.com/Mr-Loevan/HSA-DPO

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Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback

https://github.com/OpenBMB/MiniCPM-o

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MiniCPM-V: A GPT-4V Level MLLM on Your Phone

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

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

https://github.com/ParitoshParmar/HalluciNet

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HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN

https://github.com/Pints-AI/Finetune-Bench-RAG

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Finetune-RAG: Fine-Tuning Language Models to Resist Hallucination in Retrieval-Augmented Generation

https://github.com/RManLuo/graph-constrained-reasoning

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Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models

https://github.com/RUCAIBox/HaluEval

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HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models

https://github.com/ReNginx/ADeLA

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ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation

https://github.com/RezzFayyazi/ProveRAG

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ProveRAG: Provenance-Driven Vulnerability Analysis with Automated Retrieval-Augmented LLMs

https://github.com/RezzFayyazi/TTP-LLM

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Advancing TTP Analysis: Harnessing the Power of Large Language Models with Retrieval Augmented Generation

https://github.com/RicardoLuL/VaLiD_LVLMs_hallucinations

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VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding

https://github.com/RujingYao/LSIM

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Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning

https://github.com/SakethReddyVemula/semeval-2025_Mu-SHROOM

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keepitsimple at SemEval-2025 Task 3: LLM-Uncertainty based Approach for Multilingual Hallucination Span Detection

https://github.com/ShishirPatil/gorilla

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Gorilla: Large Language Model Connected with Massive APIs

https://github.com/ShootingWong/DomainRAG

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DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented Generation

https://github.com/StevenSong/multimodal-cancer-survival

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Multimodal Survival Modeling in the Age of Foundation Models

https://github.com/SunJiamei/LRP-imagecaptioning-pytorch

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Explain and Improve: LRP-Inference Fine-Tuning for Image Captioning Models

https://github.com/THU-KEG/AtomR

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AtomR: Atomic Operator-Empowered Large Language Models for Heterogeneous Knowledge Reasoning

https://github.com/THU-KEG/MAVEN-FACT

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MAVEN-Fact: A Large-scale Event Factuality Detection Dataset

https://github.com/TahsinaHashem/FaithD2T

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Generating Faithful and Salient Text from Multimodal Data

https://github.com/TencentYoutuResearch/PedestrianDetection-NohNMS

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NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination

https://github.com/Trusted-AI/adversarial-robustness-toolbox

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Weakly Supervised Detection of Hallucinations in LLM Activations

https://github.com/UB-Mannheim/FAIR-GPT

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FAIR GPT: A virtual consultant for research data management in ChatGPT

https://github.com/UKPLab/tacl2025-ood-eval-self-rationalization

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Self-Rationalization in the Wild: A Large Scale Out-of-Distribution Evaluation on NLI-related tasks

https://github.com/WorldHellow/mHallucinations-LLM

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How Much Do LLMs Hallucinate across Languages? On Multilingual Estimation of LLM Hallucination in the Wild

https://github.com/YongyiTang92/MoNet-Features

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Hallucinating Optical Flow Features for Video Classification

https://github.com/Yue-LLM-Pit/FFA

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Large Language Models Are Involuntary Truth-Tellers: Exploiting Fallacy Failure for Jailbreak Attacks

https://github.com/Ztrimus/job-llm

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ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement

https://github.com/abachaa/evaluationmetrics-acl23

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An Investigation of Evaluation Metrics for Automated Medical Note Generation

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