Guardado en:
| Autores principales: | Vamshi, Bodla Krishna, Bhatnagar, Rohan, Yang, Haizhao |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2601.06196 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Protocode: Prototype-Driven Interpretability for Code Generation in LLMs
por: Bodla, Krishna Vamshi, et al.
Publicado: (2025)
por: Bodla, Krishna Vamshi, et al.
Publicado: (2025)
Principal Prototype Analysis on Manifold for Interpretable Reinforcement Learning
por: Vamshi, Bodla Krishna, et al.
Publicado: (2026)
por: Vamshi, Bodla Krishna, et al.
Publicado: (2026)
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps
por: Chuang, Yung-Sung, et al.
Publicado: (2024)
por: Chuang, Yung-Sung, et al.
Publicado: (2024)
Scalable Token-Level Hallucination Detection in Large Language Models
por: Min, Rui, et al.
Publicado: (2026)
por: Min, Rui, et al.
Publicado: (2026)
(Im)possibility of Automated Hallucination Detection in Large Language Models
por: Karbasi, Amin, et al.
Publicado: (2025)
por: Karbasi, Amin, et al.
Publicado: (2025)
Principled Detection of Hallucinations in Large Language Models via Multiple Testing
por: Li, Jiawei, et al.
Publicado: (2025)
por: Li, Jiawei, et al.
Publicado: (2025)
Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation
por: Mündler, Niels, et al.
Publicado: (2023)
por: Mündler, Niels, et al.
Publicado: (2023)
Unified Hallucination Detection for Multimodal Large Language Models
por: Chen, Xiang, et al.
Publicado: (2024)
por: Chen, Xiang, et al.
Publicado: (2024)
Mitigating Hallucinated Translations in Large Language Models with Hallucination-focused Preference Optimization
por: Tang, Zilu, et al.
Publicado: (2025)
por: Tang, Zilu, et al.
Publicado: (2025)
MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models
por: Pandit, Shrey, et al.
Publicado: (2025)
por: Pandit, Shrey, et al.
Publicado: (2025)
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space
por: Zhang, Shaolei, et al.
Publicado: (2024)
por: Zhang, Shaolei, et al.
Publicado: (2024)
Hallucination is Inevitable: An Innate Limitation of Large Language Models
por: Xu, Ziwei, et al.
Publicado: (2024)
por: Xu, Ziwei, et al.
Publicado: (2024)
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
por: Oh, Jio, et al.
Publicado: (2024)
por: Oh, Jio, et al.
Publicado: (2024)
Learning to Reason for Hallucination Span Detection
por: Su, Hsuan, et al.
Publicado: (2025)
por: Su, Hsuan, et al.
Publicado: (2025)
Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability
por: Hron, Jiri, et al.
Publicado: (2024)
por: Hron, Jiri, et al.
Publicado: (2024)
Mitigating Hallucinations in Large Language Models via Causal Reasoning
por: Li, Yuangang, et al.
Publicado: (2025)
por: Li, Yuangang, et al.
Publicado: (2025)
DynaSpec: Context-aware Dynamic Speculative Sampling for Large-Vocabulary Language Models
por: Zhang, Jinbin, et al.
Publicado: (2025)
por: Zhang, Jinbin, et al.
Publicado: (2025)
Efficient Contrastive Decoding with Probabilistic Hallucination Detection - Mitigating Hallucinations in Large Vision Language Models -
por: Fieback, Laura, et al.
Publicado: (2025)
por: Fieback, Laura, et al.
Publicado: (2025)
FRED: Financial Retrieval-Enhanced Detection and Editing of Hallucinations in Language Models
por: Tan, Likun, et al.
Publicado: (2025)
por: Tan, Likun, et al.
Publicado: (2025)
CPR: Mitigating Large Language Model Hallucinations with Curative Prompt Refinement
por: Shim, Jung-Woo, et al.
Publicado: (2025)
por: Shim, Jung-Woo, et al.
Publicado: (2025)
Multi-stage Prompt Refinement for Mitigating Hallucinations in Large Language Models
por: Shim, Jung-Woo, et al.
Publicado: (2025)
por: Shim, Jung-Woo, et al.
Publicado: (2025)
Prompt-Response Semantic Divergence Metrics for Faithfulness Hallucination and Misalignment Detection in Large Language Models
por: Halperin, Igor
Publicado: (2025)
por: Halperin, Igor
Publicado: (2025)
Active Layer-Contrastive Decoding Reduces Hallucination in Large Language Model Generation
por: Zhang, Hongxiang, et al.
Publicado: (2025)
por: Zhang, Hongxiang, et al.
Publicado: (2025)
Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models
por: Dey, Prasenjit, et al.
Publicado: (2025)
por: Dey, Prasenjit, et al.
Publicado: (2025)
Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination
por: Song, Jongyoon, et al.
Publicado: (2024)
por: Song, Jongyoon, et al.
Publicado: (2024)
LLMs Meet Finance: Fine-Tuning Foundation Models for the Open FinLLM Leaderboard
por: Rao, Varun, et al.
Publicado: (2025)
por: Rao, Varun, et al.
Publicado: (2025)
Large Language Models are Miscalibrated In-Context Learners
por: Li, Chengzu, et al.
Publicado: (2023)
por: Li, Chengzu, et al.
Publicado: (2023)
Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
por: Rahman, Subhey Sadi, et al.
Publicado: (2025)
por: Rahman, Subhey Sadi, et al.
Publicado: (2025)
Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning
por: Wang, Shengyuan, et al.
Publicado: (2025)
por: Wang, Shengyuan, et al.
Publicado: (2025)
Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification
por: Kang, Haoqiang, et al.
Publicado: (2023)
por: Kang, Haoqiang, et al.
Publicado: (2023)
Detecting Hallucinations in Large Language Model Generation: A Token Probability Approach
por: Quevedo, Ernesto, et al.
Publicado: (2024)
por: Quevedo, Ernesto, et al.
Publicado: (2024)
On Mitigating Code LLM Hallucinations with API Documentation
por: Jain, Nihal, et al.
Publicado: (2024)
por: Jain, Nihal, et al.
Publicado: (2024)
Neural Diversity Regularizes Hallucinations in Language Models
por: Chakrabarti, Kushal, et al.
Publicado: (2025)
por: Chakrabarti, Kushal, et al.
Publicado: (2025)
The Role of Diversity in In-Context Learning for Large Language Models
por: Xiao, Wenyang, et al.
Publicado: (2025)
por: Xiao, Wenyang, et al.
Publicado: (2025)
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning
por: Wang, Xinyi, et al.
Publicado: (2023)
por: Wang, Xinyi, et al.
Publicado: (2023)
Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
por: Zhang, Yue, et al.
Publicado: (2023)
por: Zhang, Yue, et al.
Publicado: (2023)
SALMAN: Stability Analysis of Language Models Through the Maps Between Graph-based Manifolds
por: Cheng, Wuxinlin, et al.
Publicado: (2025)
por: Cheng, Wuxinlin, et al.
Publicado: (2025)
On the Fundamental Impossibility of Hallucination Control in Large Language Models
por: Karpowicz, Michał P.
Publicado: (2025)
por: Karpowicz, Michał P.
Publicado: (2025)
Woodpecker: Hallucination Correction for Multimodal Large Language Models
por: Yin, Shukang, et al.
Publicado: (2023)
por: Yin, Shukang, et al.
Publicado: (2023)
In-context Autoencoder for Context Compression in a Large Language Model
por: Ge, Tao, et al.
Publicado: (2023)
por: Ge, Tao, et al.
Publicado: (2023)
Ejemplares similares
-
Protocode: Prototype-Driven Interpretability for Code Generation in LLMs
por: Bodla, Krishna Vamshi, et al.
Publicado: (2025) -
Principal Prototype Analysis on Manifold for Interpretable Reinforcement Learning
por: Vamshi, Bodla Krishna, et al.
Publicado: (2026) -
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps
por: Chuang, Yung-Sung, et al.
Publicado: (2024) -
Scalable Token-Level Hallucination Detection in Large Language Models
por: Min, Rui, et al.
Publicado: (2026) -
(Im)possibility of Automated Hallucination Detection in Large Language Models
por: Karbasi, Amin, et al.
Publicado: (2025)