Image de couverture de livre

Less is More for Improving Automatic Evaluation of Factual Consistency

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Wang, Tong, Kulkarni, Ninad, Qi, Yanjun
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language Artificial Intelligence Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

TaeBench: Improving Quality of Toxic Adversarial Examples
par: Zhu, Xuan, et autres
Publié: (2024)

Less is More: Improving LLM Alignment via Preference Data Selection
par: Deng, Xun, et autres
Publié: (2025)

Probabilistic Consensus through Ensemble Validation: A Framework for LLM Reliability
par: Naik, Ninad
Publié: (2024)

LIMR: Less is More for RL Scaling
par: Li, Xuefeng, et autres
Publié: (2025)

Cross-Lingual Consistency of Factual Knowledge in Multilingual Language Models
par: Qi, Jirui, et autres
Publié: (2023)

When More is Less: Understanding Chain-of-Thought Length in LLMs
par: Wu, Yuyang, et autres
Publié: (2025)

Integrative Decoding: Improve Factuality via Implicit Self-consistency
par: Cheng, Yi, et autres
Publié: (2024)

Supernova: Achieving More with Less in Transformer Architectures
par: Tanase, Andrei-Valentin, et autres
Publié: (2025)

Stress Testing Factual Consistency Metrics for Long-Document Summarization
par: Mujahid, Zain Muhammad, et autres
Publié: (2025)

Input-Time Scaling: Adding Noise and Irrelevance into Less-Is-More Drastically Improves Reasoning Performance and Efficiency
par: Huang, Rapheal, et autres
Publié: (2025)

Knowledge-Level Consistency Reinforcement Learning: Dual-Fact Alignment for Long-Form Factuality
par: Li, Junliang, et autres
Publié: (2025)

Less is More: Denoising Knowledge Graphs For Retrieval Augmented Generation
par: Zheng, Yilun, et autres
Publié: (2025)

Less is More: Local Intrinsic Dimensions of Contextual Language Models
par: Ruppik, Benjamin Matthias, et autres
Publié: (2025)

Learn More, Forget Less: A Gradient-Aware Data Selection Approach for LLM
par: Liu, Yibai, et autres
Publié: (2025)

Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation
par: Riaz, Haris, et autres
Publié: (2025)

Towards a Holistic Evaluation of LLMs on Factual Knowledge Recall
par: Yuan, Jiaqing, et autres
Publié: (2024)

Explain Less, Understand More: Jargon Detection via Personalized Parameter-Efficient Fine-tuning
par: Wu, Bohao, et autres
Publié: (2025)

Self-Training Meets Consistency: Improving LLMs' Reasoning with Consistency-Driven Rationale Evaluation
par: Lee, Jaehyeok, et autres
Publié: (2024)

Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification
par: Guo, Yiju, et autres
Publié: (2026)

Adaptive Conformal Prediction for Improving Factuality of Generations by Large Language Models
par: Rubashevskii, Aleksandr, et autres
Publié: (2026)

Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains
par: Ramprasad, Sanjana, et autres
Publié: (2024)

Should We Attend More or Less? Modulating Attention for Fairness
par: Zayed, Abdelrahman, et autres
Publié: (2023)

Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs
par: Liu, Xiaoze, et autres
Publié: (2024)

Less is More: Extreme Gradient Boost Rank-1 Adaption for Efficient Finetuning of LLMs
par: Zhang, Yifei, et autres
Publié: (2024)

Towards Improved Preference Optimization Pipeline: from Data Generation to Budget-Controlled Regularization
par: Chen, Zhuotong, et autres
Publié: (2024)

SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Models
par: Zhang, Jianyi, et autres
Publié: (2024)

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
par: Chuang, Yung-Sung, et autres
Publié: (2023)

Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend
par: Lu, Ning, et autres
Publié: (2023)

Disambiguation-Centric Finetuning Makes Enterprise Tool-Calling LLMs More Realistic and Less Risky
par: Hathidara, Ashutosh, et autres
Publié: (2025)

Graph of Attacks with Pruning: Optimizing Stealthy Jailbreak Prompt Generation for Enhanced LLM Content Moderation
par: Schwartz, Daniel, et autres
Publié: (2025)

ConsistRM: Improving Generative Reward Models via Consistency-Aware Self-Training
par: Liang, Yu, et autres
Publié: (2026)

FECT: Factuality Evaluation of Interpretive AI-Generated Claims in Contact Center Conversation Transcripts
par: Shin, Hagyeong, et autres
Publié: (2025)

Hallucination to Truth: A Review of Fact-Checking and Factuality Evaluation in Large Language Models
par: Rahman, Subhey Sadi, et autres
Publié: (2025)

Zero-knowledge LLM hallucination detection and mitigation through fine-grained cross-model consistency
par: Goel, Aman, et autres
Publié: (2025)

LoRA Learns Less and Forgets Less
par: Biderman, Dan, et autres
Publié: (2024)

Soft Self-Consistency Improves Language Model Agents
par: Wang, Han, et autres
Publié: (2024)

BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs
par: Yang, Junxiao, et autres
Publié: (2025)

Language Models with Conformal Factuality Guarantees
par: Mohri, Christopher, et autres
Publié: (2024)

Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation
par: Wang, Zixin, et autres
Publié: (2024)

Benchmarking Multi-Agent LLM Architectures for Financial Document Processing: A Comparative Study of Orchestration Patterns, Cost-Accuracy Tradeoffs and Production Scaling Strategies
par: Kulkarni, Siddhant, et autres
Publié: (2026)