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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/promptslab/rosettaeval

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Gemini Goes to Med School: Exploring the Capabilities of Multimodal Large Language Models on Medical Challenge Problems & Hallucinations

https://github.com/pspdada/SENTINEL

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Mitigating Object Hallucinations via Sentence-Level Early Intervention

https://github.com/psunlpgroup/verbosityllm

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Verbosity $\neq$ Veracity: Demystify Verbosity Compensation Behavior of Large Language Models

https://github.com/purdue-m2/medchat

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MedChat: A Multi-Agent Framework for Multimodal Diagnosis with Large Language Models

https://github.com/qiancheng0/ekd_impacts_pkg

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"Merge Conflicts!" Exploring the Impacts of External Distractors to Parametric Knowledge Graphs

https://github.com/qinyu-allen-zhao/lvlm-lp

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The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models?

https://github.com/qizhou000/DAFNet

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DAFNet: Dynamic Auxiliary Fusion for Sequential Model Editing in Large Language Models

https://github.com/qqplot/dcpmi

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Mitigating Hallucination in Abstractive Summarization with Domain-Conditional Mutual Information

https://github.com/quangpham2006/SmallPlan

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SmallPlan: Leverage Small Language Models for Sequential Path Planning with Simulation-Powered, LLM-Guided Distillation

https://github.com/quqxui/medlasa

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Editing Factual Knowledge and Explanatory Ability of Medical Large Language Models

https://github.com/rainbowluocs/deem

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DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception

https://github.com/razvanip13/towards_lighter_and_robust_evaluation

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Towards Lighter and Robust Evaluation for Retrieval Augmented Generation

https://github.com/reds-lab/preference-learning-with-rationales

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Data-Centric Human Preference Optimization with Rationales

https://github.com/responsibleailab/halo

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HALO: Hallucination Analysis and Learning Optimization to Empower LLMs with Retrieval-Augmented Context for Guided Clinical Decision Making

https://github.com/rh-dang/ecbench

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ECBench: Can Multi-modal Foundation Models Understand the Egocentric World? A Holistic Embodied Cognition Benchmark

https://github.com/richard-peng-xia/mmed-rag

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MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models

https://github.com/rlhf-v/rlaif-v

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RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness

https://github.com/rlhf-v/rlhf-v

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RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback

https://github.com/robertlakatos/ragvsfn

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Investigating the performance of Retrieval-Augmented Generation and fine-tuning for the development of AI-driven knowledge-based systems

https://github.com/robot2050/attenhscore

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Invoke Interfaces Only When Needed: Adaptive Invocation for Large Language Models in Question Answering

https://github.com/romanlee6/multi_LLM_comm

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Theory of Mind for Multi-Agent Collaboration via Large Language Models

https://github.com/rucaibox/bamboo

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BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models

https://github.com/rucaibox/haluagent

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Small Agent Can Also Rock! Empowering Small Language Models as Hallucination Detector

https://github.com/rucaibox/halueval-2.0

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The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models

https://github.com/rucaibox/helma

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

https://github.com/rucaibox/pope

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Evaluating Object Hallucination in Large Vision-Language Models

https://github.com/russellyq/medhalltune

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MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language Models

https://github.com/s-nlp/shroom

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SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination Detection

https://github.com/salesforceairesearch/answer-engine-eval

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Search Engines in an AI Era: The False Promise of Factual and Verifiable Source-Cited Responses

https://github.com/salesforceairesearch/auto-cei

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Automatic Curriculum Expert Iteration for Reliable LLM Reasoning

https://github.com/salesforceairesearch/faitheval

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FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"

https://github.com/sam575/axial-gan

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Simultaneous Face Hallucination and Translation for Thermal to Visible Face Verification using Axial-GAN

https://github.com/sammarfy/vlm4bio

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VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images

https://github.com/scofield7419/ummt-vsh

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Scene Graph as Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene Hallucination

https://github.com/seasonyao/learnfromhumanedit

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Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization

https://github.com/seemdog/DAHL

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DAHL: Domain-specific Automated Hallucination Evaluation of Long-Form Text through a Benchmark Dataset in Biomedicine

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