FLAME: Factuality-Aware Alignment for Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Sheng-Chieh, Gao, Luyu, Oguz, Barlas, Xiong, Wenhan, Lin, Jimmy, Yih, Wen-tau, Chen, Xilun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers
by: Ma, Xueguang, et al.
Published: (2025)
by: Ma, Xueguang, et al.
Published: (2025)
Learning Facts at Scale with Active Reading
by: Lin, Jessy, et al.
Published: (2025)
by: Lin, Jessy, et al.
Published: (2025)
Learning to Reason for Factuality
by: Chen, Xilun, et al.
Published: (2025)
by: Chen, Xilun, et al.
Published: (2025)
Memory Layers at Scale
by: Berges, Vincent-Pierre, et al.
Published: (2024)
by: Berges, Vincent-Pierre, et al.
Published: (2024)
FACTORY: A Challenging Human-Verified Prompt Set for Long-Form Factuality
by: Chen, Mingda, et al.
Published: (2025)
by: Chen, Mingda, et al.
Published: (2025)
SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
by: Chuang, Yung-Sung, et al.
Published: (2025)
by: Chuang, Yung-Sung, et al.
Published: (2025)
Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering
by: Chen, Mingda, et al.
Published: (2023)
by: Chen, Mingda, et al.
Published: (2023)
Continual Learning via Sparse Memory Finetuning
by: Lin, Jessy, et al.
Published: (2025)
by: Lin, Jessy, et al.
Published: (2025)
Post-training an LLM for RAG? Train on Self-Generated Demonstrations
by: Finlayson, Matthew, et al.
Published: (2025)
by: Finlayson, Matthew, et al.
Published: (2025)
FactAlign: Long-form Factuality Alignment of Large Language Models
by: Huang, Chao-Wei, et al.
Published: (2024)
by: Huang, Chao-Wei, et al.
Published: (2024)
Unveiling Factual Recall Behaviors of Large Language Models through Knowledge Neurons
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
Nearest Neighbor Speculative Decoding for LLM Generation and Attribution
by: Li, Minghan, et al.
Published: (2024)
by: Li, Minghan, et al.
Published: (2024)
Reliable, Adaptable, and Attributable Language Models with Retrieval
by: Asai, Akari, et al.
Published: (2024)
by: Asai, Akari, et al.
Published: (2024)
Instruction-tuned Language Models are Better Knowledge Learners
by: Jiang, Zhengbao, et al.
Published: (2024)
by: Jiang, Zhengbao, et al.
Published: (2024)
Beyond Under-Alignment: Atomic Preference Enhanced Factuality Tuning for Large Language Models
by: Yuan, Hongbang, et al.
Published: (2024)
by: Yuan, Hongbang, et al.
Published: (2024)
PrismRAG: Boosting RAG Factuality with Distractor Resilience and Strategized Reasoning
by: Kachuee, Mohammad, et al.
Published: (2025)
by: Kachuee, Mohammad, et al.
Published: (2025)
Editing Factual Knowledge and Explanatory Ability of Medical Large Language Models
by: Xu, Derong, et al.
Published: (2024)
by: Xu, Derong, et al.
Published: (2024)
FLAME: Financial Large-Language Model Assessment and Metrics Evaluation
by: Guo, Jiayu, et al.
Published: (2025)
by: Guo, Jiayu, et al.
Published: (2025)
Factuality of Large Language Models: A Survey
by: Wang, Yuxia, et al.
Published: (2024)
by: Wang, Yuxia, et al.
Published: (2024)
Towards Safety and Helpfulness Balanced Responses via Controllable Large Language Models
by: Tuan, Yi-Lin, et al.
Published: (2024)
by: Tuan, Yi-Lin, et al.
Published: (2024)
Enhancing Large Language Model for Knowledge Graph Completion via Structure-Aware Alignment-Tuning
by: Liu, Yu, et al.
Published: (2025)
by: Liu, Yu, et al.
Published: (2025)
Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs
by: Liu, Xiaoze, et al.
Published: (2024)
by: Liu, Xiaoze, et al.
Published: (2024)
Mitigating Hidden Confounding by Progressive Confounder Imputation via Large Language Models
by: Yang, Hao, et al.
Published: (2025)
by: Yang, Hao, et al.
Published: (2025)
Reasoning Factual Knowledge in Structured Data with Large Language Models
by: Huang, Sirui, et al.
Published: (2024)
by: Huang, Sirui, et al.
Published: (2024)
LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models
by: Han, Chi, et al.
Published: (2023)
by: Han, Chi, et al.
Published: (2023)
Reasoning Models Hallucinate More: Factuality-Aware Reinforcement Learning for Large Reasoning Models
by: Li, Junyi, et al.
Published: (2025)
by: Li, Junyi, et al.
Published: (2025)
Answer, Refuse, or Guess? Investigating Risk-Aware Decision Making in Language Models
by: Wu, Cheng-Kuang, et al.
Published: (2025)
by: Wu, Cheng-Kuang, et al.
Published: (2025)
Factuality Challenges in the Era of Large Language Models
by: Augenstein, Isabelle, et al.
Published: (2023)
by: Augenstein, Isabelle, et al.
Published: (2023)
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
by: Nie, Fan, et al.
Published: (2024)
by: Nie, Fan, et al.
Published: (2024)
LEAF: Learning and Evaluation Augmented by Fact-Checking to Improve Factualness in Large Language Models
by: Tran, Hieu, et al.
Published: (2024)
by: Tran, Hieu, et al.
Published: (2024)
The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality
by: Cheng, Aileen, et al.
Published: (2025)
by: Cheng, Aileen, et al.
Published: (2025)
Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning
by: Fu, Rao, et al.
Published: (2024)
by: Fu, Rao, et al.
Published: (2024)
Entity Alignment with Noisy Annotations from Large Language Models
by: Chen, Shengyuan, et al.
Published: (2024)
by: Chen, Shengyuan, et al.
Published: (2024)
Factual Self-Awareness in Language Models: Representation, Robustness, and Scaling
by: Tamoyan, Hovhannes, et al.
Published: (2025)
by: Tamoyan, Hovhannes, et al.
Published: (2025)
Cracking Factual Knowledge: A Comprehensive Analysis of Degenerate Knowledge Neurons in Large Language Models
by: Chen, Yuheng, et al.
Published: (2024)
by: Chen, Yuheng, et al.
Published: (2024)
Extracting and Understanding the Superficial Knowledge in Alignment
by: Chen, Runjin, et al.
Published: (2025)
by: Chen, Runjin, et al.
Published: (2025)
Language Models' Factuality Depends on the Language of Inquiry
by: Aggarwal, Tushar, et al.
Published: (2025)
by: Aggarwal, Tushar, et al.
Published: (2025)
MuBench: Assessment of Multilingual Capabilities of Large Language Models Across 61 Languages
by: Han, Wenhan, et al.
Published: (2025)
by: Han, Wenhan, et al.
Published: (2025)
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
by: Sukhbaatar, Sainbayar, et al.
Published: (2024)
by: Sukhbaatar, Sainbayar, et al.
Published: (2024)
ACER: Automatic Language Model Context Extension via Retrieval
by: Gao, Luyu, et al.
Published: (2024)
by: Gao, Luyu, et al.
Published: (2024)
Similar Items
-
DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers
by: Ma, Xueguang, et al.
Published: (2025) -
Learning Facts at Scale with Active Reading
by: Lin, Jessy, et al.
Published: (2025) -
Learning to Reason for Factuality
by: Chen, Xilun, et al.
Published: (2025) -
Memory Layers at Scale
by: Berges, Vincent-Pierre, et al.
Published: (2024) -
FACTORY: A Challenging Human-Verified Prompt Set for Long-Form Factuality
by: Chen, Mingda, et al.
Published: (2025)