SOTAVerified

Hallucination

Papers

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Showing 601–625 of 1816 papers

TitleStatusHype
Black-Box Visual Prompt Engineering for Mitigating Object Hallucination in Large Vision Language Models—0
MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness—0
Can LLMs Detect Intrinsic Hallucinations in Paraphrasing and Machine Translation?—0
Hallucination by Code Generation LLMs: Taxonomy, Benchmarks, Mitigation, and Challenges—0
An Automated Reinforcement Learning Reward Design Framework with Large Language Model for Cooperative Platoon Coordination—0
Explanatory Summarization with Discourse-Driven Planning—0
Validating Network Protocol Parsers with Traceable RFC Document Interpretation—0
Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction—0
Toward Personalizing Quantum Computing Education: An Evolutionary LLM-Powered Approach—0
(Im)possibility of Automated Hallucination Detection in Large Language Models—0
The Dance of Atoms-De Novo Protein Design with Diffusion Model—0
Insights from Verification: Training a Verilog Generation LLM with Reinforcement Learning with Testbench Feedback—0
Grounded in Context: Retrieval-Based Method for Hallucination Detection—0
POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications—0
aiXamine: Simplified LLM Safety and Security—0
ResNetVLLM-2: Addressing ResNetVLLM's Multi-Modal Hallucinations—0
Density Measures for Language Generation—0
Hydra: An Agentic Reasoning Approach for Enhancing Adversarial Robustness and Mitigating Hallucinations in Vision-Language Models—0
Multi-Stage Retrieval for Operational Technology Cybersecurity Compliance Using Large Language Models: A Railway Casestudy—0
Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training—0
QLLM: Do We Really Need a Mixing Network for Credit Assignment in Multi-Agent Reinforcement Learning?—0
Aspect-Based Summarization with Self-Aspect Retrieval Enhanced Generation—0
Why and How LLMs Hallucinate: Connecting the Dots with Subsequence AssociationsCode0
Efficient Contrastive Decoding with Probabilistic Hallucination Detection - Mitigating Hallucinations in Large Vision Language Models -—0
Self-alignment of Large Video Language Models with Refined Regularized Preference Optimization—0
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