Saved in:
| Main Authors: | Chakrabarti, Kushal, Balachundhar, Nirmal |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.20690 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multi-Head Attention Is a Multi-Player Game
by: Chakrabarti, Kushal, et al.
Published: (2026)
by: Chakrabarti, Kushal, et al.
Published: (2026)
Unraveling the cognitive patterns of Large Language Models through module communities
by: Bhandari, Kushal Raj, et al.
Published: (2025)
by: Bhandari, Kushal Raj, et al.
Published: (2025)
Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales
by: Nirmal, Ayushi, et al.
Published: (2024)
by: Nirmal, Ayushi, et al.
Published: (2024)
Mitigating Hallucinated Translations in Large Language Models with Hallucination-focused Preference Optimization
by: Tang, Zilu, et al.
Published: (2025)
by: Tang, Zilu, et al.
Published: (2025)
Hallucination Diversity-Aware Active Learning for Text Summarization
by: Xia, Yu, et al.
Published: (2024)
by: Xia, Yu, et al.
Published: (2024)
A Critical Evaluation of AI Feedback for Aligning Large Language Models
by: Sharma, Archit, et al.
Published: (2024)
by: Sharma, Archit, et al.
Published: (2024)
Hallucination is Inevitable: An Innate Limitation of Large Language Models
by: Xu, Ziwei, et al.
Published: (2024)
by: Xu, Ziwei, et al.
Published: (2024)
(Im)possibility of Automated Hallucination Detection in Large Language Models
by: Karbasi, Amin, et al.
Published: (2025)
by: Karbasi, Amin, et al.
Published: (2025)
Mitigating Hallucinations in Large Language Models via Causal Reasoning
by: Li, Yuangang, et al.
Published: (2025)
by: Li, Yuangang, et al.
Published: (2025)
Scalable Token-Level Hallucination Detection in Large Language Models
by: Min, Rui, et al.
Published: (2026)
by: Min, Rui, et al.
Published: (2026)
Unfamiliar Finetuning Examples Control How Language Models Hallucinate
by: Kang, Katie, et al.
Published: (2024)
by: Kang, Katie, et al.
Published: (2024)
Transcoders Trace Visual Grounding and Hallucinations in Vision-Language Models
by: Damianos, Dimitrios, et al.
Published: (2026)
by: Damianos, Dimitrios, et al.
Published: (2026)
Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability
by: Hron, Jiri, et al.
Published: (2024)
by: Hron, Jiri, et al.
Published: (2024)
FRED: Financial Retrieval-Enhanced Detection and Editing of Hallucinations in Language Models
by: Tan, Likun, et al.
Published: (2025)
by: Tan, Likun, et al.
Published: (2025)
CPR: Mitigating Large Language Model Hallucinations with Curative Prompt Refinement
by: Shim, Jung-Woo, et al.
Published: (2025)
by: Shim, Jung-Woo, et al.
Published: (2025)
Principled Detection of Hallucinations in Large Language Models via Multiple Testing
by: Li, Jiawei, et al.
Published: (2025)
by: Li, Jiawei, et al.
Published: (2025)
Multi-stage Prompt Refinement for Mitigating Hallucinations in Large Language Models
by: Shim, Jung-Woo, et al.
Published: (2025)
by: Shim, Jung-Woo, et al.
Published: (2025)
Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation
by: Mündler, Niels, et al.
Published: (2023)
by: Mündler, Niels, et al.
Published: (2023)
Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models
by: Ferrando, Javier, et al.
Published: (2024)
by: Ferrando, Javier, et al.
Published: (2024)
Manifold-based Sampling for In-Context Hallucination Detection in Large Language Models
by: Vamshi, Bodla Krishna, et al.
Published: (2026)
by: Vamshi, Bodla Krishna, et al.
Published: (2026)
Active Layer-Contrastive Decoding Reduces Hallucination in Large Language Model Generation
by: Zhang, Hongxiang, et al.
Published: (2025)
by: Zhang, Hongxiang, et al.
Published: (2025)
Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models
by: Dey, Prasenjit, et al.
Published: (2025)
by: Dey, Prasenjit, et al.
Published: (2025)
TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space
by: Zhang, Shaolei, et al.
Published: (2024)
by: Zhang, Shaolei, et al.
Published: (2024)
Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination
by: Song, Jongyoon, et al.
Published: (2024)
by: Song, Jongyoon, et al.
Published: (2024)
HD-NDEs: Neural Differential Equations for Hallucination Detection in LLMs
by: Li, Qing, et al.
Published: (2025)
by: Li, Qing, et al.
Published: (2025)
Information Guided Regularization for Fine-tuning Language Models
by: Sharma, Mandar, et al.
Published: (2024)
by: Sharma, Mandar, et al.
Published: (2024)
Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
by: Rahman, Subhey Sadi, et al.
Published: (2025)
by: Rahman, Subhey Sadi, et al.
Published: (2025)
MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models
by: Pandit, Shrey, et al.
Published: (2025)
by: Pandit, Shrey, et al.
Published: (2025)
Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning
by: Wang, Shengyuan, et al.
Published: (2025)
by: Wang, Shengyuan, et al.
Published: (2025)
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
by: Oh, Jio, et al.
Published: (2024)
by: Oh, Jio, et al.
Published: (2024)
Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification
by: Kang, Haoqiang, et al.
Published: (2023)
by: Kang, Haoqiang, et al.
Published: (2023)
Confidence Regularized Masked Language Modeling using Text Length
by: Ji, Seunghyun, et al.
Published: (2025)
by: Ji, Seunghyun, et al.
Published: (2025)
Text Quality-Based Pruning for Efficient Training of Language Models
by: Sharma, Vasu, et al.
Published: (2024)
by: Sharma, Vasu, et al.
Published: (2024)
Diversity-oriented Data Augmentation with Large Language Models
by: Wang, Zaitian, et al.
Published: (2025)
by: Wang, Zaitian, et al.
Published: (2025)
The Role of Diversity in In-Context Learning for Large Language Models
by: Xiao, Wenyang, et al.
Published: (2025)
by: Xiao, Wenyang, et al.
Published: (2025)
Flaming-hot Initiation with Regular Execution Sampling for Large Language Models
by: Chen, Weizhe, et al.
Published: (2024)
by: Chen, Weizhe, et al.
Published: (2024)
On the Expressiveness and Length Generalization of Selective State-Space Models on Regular Languages
by: Terzić, Aleksandar, et al.
Published: (2024)
by: Terzić, Aleksandar, et al.
Published: (2024)
The Phenomenology of Hallucinations
by: Ruscio, Valeria, et al.
Published: (2026)
by: Ruscio, Valeria, et al.
Published: (2026)
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps
by: Chuang, Yung-Sung, et al.
Published: (2024)
by: Chuang, Yung-Sung, et al.
Published: (2024)
Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
by: Zhang, Yue, et al.
Published: (2023)
by: Zhang, Yue, et al.
Published: (2023)
Similar Items
-
Multi-Head Attention Is a Multi-Player Game
by: Chakrabarti, Kushal, et al.
Published: (2026) -
Unraveling the cognitive patterns of Large Language Models through module communities
by: Bhandari, Kushal Raj, et al.
Published: (2025) -
Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales
by: Nirmal, Ayushi, et al.
Published: (2024) -
Mitigating Hallucinated Translations in Large Language Models with Hallucination-focused Preference Optimization
by: Tang, Zilu, et al.
Published: (2025) -
Hallucination Diversity-Aware Active Learning for Text Summarization
by: Xia, Yu, et al.
Published: (2024)