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Hallucination

Papers

Showing 10261050 of 1816 papers

TitleStatusHype
Fact :Teaching MLLMs with Faithful, Concise and Transferable Rationales0
Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities0
Feature Hallucination for Self-supervised Action Recognition0
Less for More: Enhanced Feedback-aligned Mixed LLMs for Molecule Caption Generation and Fine-Grained NLI Evaluation0
Fewer Truncations Improve Language Modeling0
Few-Shot Learning via Saliency-guided Hallucination of Samples0
Few-Shot Optimized Framework for Hallucination Detection in Resource-Limited NLP Systems0
FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping0
FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback0
FH-GAN: Face Hallucination and Recognition using Generative Adversarial Network0
Fine-Grained Guidance for Retrievers: Leveraging LLMs' Feedback in Retrieval-Augmented Generation0
Fine-grained Hallucination Detection and Editing for Language Models0
FG-PRM: Fine-grained Hallucination Detection and Mitigation in Language Model Mathematical Reasoning0
FINEMATCH: Aspect-based Fine-grained Image and Text Mismatch Detection and Correction0
Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy0
Fine-Tuning Vision-Language Model for Automated Engineering Drawing Information Extraction0
FiSTECH: Financial Style Transfer to Enhance Creativity without Hallucinations in LLMs0
FLAME: Factuality-Aware Alignment for Large Language Models0
FlippedRAG: Black-Box Opinion Manipulation Adversarial Attacks to Retrieval-Augmented Generation Models0
Flow Dynamics Correction for Action Recognition0
FoodGPT: A Large Language Model in Food Testing Domain with Incremental Pre-training and Knowledge Graph Prompt0
Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors0
Foundations of GenIR0
Foundations of Unknown-aware Machine Learning0
FRAG: A Flexible Modular Framework for Retrieval-Augmented Generation based on Knowledge Graphs0
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