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Hallucination

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Showing 751–775 of 1816 papers

TitleStatusHype
HalluShift: Measuring Distribution Shifts towards Hallucination Detection in LLMsCode0
Handling Ontology Gaps in Semantic ParsingCode0
SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination DetectionCode0
Enhancing Retrieval Processes for Language Generation with Augmented Queries—0
Enhancing RAG with Active Learning on Conversation Records: Reject Incapables and Answer Capables—0
Can We Catch the Elephant? A Survey of the Evolvement of Hallucination Evaluation on Natural Language Generation—0
From Training-Free to Adaptive: Empirical Insights into MLLMs' Understanding of Detection Information—0
Can Structured Data Reduce Epistemic Uncertainty?—0
Enhancing Multi-Agent Consensus through Third-Party LLM Integration: Analyzing Uncertainty and Mitigating Hallucinations in Large Language Models—0
Enhancing Mathematical Reasoning in Large Language Models with Self-Consistency-Based Hallucination Detection—0
Can Open-source LLMs Enhance Data Synthesis for Toxic Detection?: An Experimental Study—0
Enhancing LLM Generation with Knowledge Hypergraph for Evidence-Based Medicine—0
Can LLMs Detect Intrinsic Hallucinations in Paraphrasing and Machine Translation?—0
Applying RLAIF for Code Generation with API-usage in Lightweight LLMs—0
Enhancing Hallucination Detection through Noise Injection—0
Enhancing Guardrails for Safe and Secure Healthcare AI—0
Enhancing Emergency Decision-making with Knowledge Graphs and Large Language Models—0
Can LLM be a Good Path Planner based on Prompt Engineering? Mitigating the Hallucination for Path Planning—0
Applications of Large Language Model Reasoning in Feature Generation—0
Enhanced Hallucination Detection in Neural Machine Translation through Simple Detector Aggregation—0
Enhanced document retrieval with topic embeddings—0
Can Large Language Models Play Games? A Case Study of A Self-Play Approach—0
Endowing Embodied Agents with Spatial Reasoning Capabilities for Vision-and-Language Navigation—0
Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study over Open-ended Question Answering—0
A Perspective for Adapting Generalist AI to Specialized Medical AI Applications and Their Challenges—0
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