Saved in:
| Main Authors: | Zhang, Yue, Zuo, Jingxuan, Su, Ke, Jing, Liqiang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.11414 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FineSurE: Fine-grained Summarization Evaluation using LLMs
by: Song, Hwanjun, et al.
Published: (2024)
by: Song, Hwanjun, et al.
Published: (2024)
Improving Model Factuality with Fine-grained Critique-based Evaluator
by: Xie, Yiqing, et al.
Published: (2024)
by: Xie, Yiqing, et al.
Published: (2024)
FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
by: Jing, Liqiang, et al.
Published: (2024)
by: Jing, Liqiang, et al.
Published: (2024)
PlainQAFact: Retrieval-augmented Factual Consistency Evaluation Metric for Biomedical Plain Language Summarization
by: You, Zhiwen, et al.
Published: (2025)
by: You, Zhiwen, et al.
Published: (2025)
QAPyramid: Fine-grained Evaluation of Content Selection for Text Summarization
by: Zhang, Shiyue, et al.
Published: (2024)
by: Zhang, Shiyue, et al.
Published: (2024)
mFACE: Multilingual Summarization with Factual Consistency Evaluation
by: Aharoni, Roee, et al.
Published: (2022)
by: Aharoni, Roee, et al.
Published: (2022)
Mask-DPO: Generalizable Fine-grained Factuality Alignment of LLMs
by: Gu, Yuzhe, et al.
Published: (2025)
by: Gu, Yuzhe, et al.
Published: (2025)
Can Large Vision-Language Models Understand Multimodal Sarcasm?
by: Wang, Xinyu, et al.
Published: (2025)
by: Wang, Xinyu, et al.
Published: (2025)
ReFEree: Reference-Free and Fine-Grained Method for Evaluating Factual Consistency in Real-World Code Summarization
by: Bae, Suyoung, et al.
Published: (2026)
by: Bae, Suyoung, et al.
Published: (2026)
SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models
by: Cheng, Xianfu, et al.
Published: (2025)
by: Cheng, Xianfu, et al.
Published: (2025)
On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization
by: Flores, Lorenzo Jaime Yu, et al.
Published: (2024)
by: Flores, Lorenzo Jaime Yu, et al.
Published: (2024)
FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence
by: Joseph, Sebastian Antony, et al.
Published: (2024)
by: Joseph, Sebastian Antony, et al.
Published: (2024)
DiVA: Fine-grained Factuality Verification with Agentic-Discriminative Verifier
by: Huang, Hui, et al.
Published: (2026)
by: Huang, Hui, et al.
Published: (2026)
Revisiting Metric Reliability for Fine-grained Evaluation of Machine Translation and Summarization in Indian Languages
by: Yari, Amir Hossein, et al.
Published: (2025)
by: Yari, Amir Hossein, et al.
Published: (2025)
ISQA: Informative Factuality Feedback for Scientific Summarization
by: Li, Zekai, et al.
Published: (2024)
by: Li, Zekai, et al.
Published: (2024)
Agent-as-Judge for Factual Summarization of Long Narratives
by: Jeong, Yeonseok, et al.
Published: (2025)
by: Jeong, Yeonseok, et al.
Published: (2025)
BanglaSummEval: Reference-Free Factual Consistency Evaluation for Bangla Summarization
by: Rafid, Ahmed, et al.
Published: (2026)
by: Rafid, Ahmed, et al.
Published: (2026)
AMRFact: Enhancing Summarization Factuality Evaluation with AMR-Driven Negative Samples Generation
by: Qiu, Haoyi, et al.
Published: (2023)
by: Qiu, Haoyi, et al.
Published: (2023)
Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models
by: Song, Jongyoon, et al.
Published: (2024)
by: Song, Jongyoon, et al.
Published: (2024)
Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization
by: Zhong, Yang, et al.
Published: (2025)
by: Zhong, Yang, et al.
Published: (2025)
Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains
by: Ramprasad, Sanjana, et al.
Published: (2024)
by: Ramprasad, Sanjana, et al.
Published: (2024)
MM-MATH: Advancing Multimodal Math Evaluation with Process Evaluation and Fine-grained Classification
by: Sun, Kai, et al.
Published: (2024)
by: Sun, Kai, et al.
Published: (2024)
XATU: A Fine-grained Instruction-based Benchmark for Explainable Text Updates
by: Zhang, Haopeng, et al.
Published: (2023)
by: Zhang, Haopeng, et al.
Published: (2023)
A Unified Hallucination Mitigation Framework for Large Vision-Language Models
by: Chang, Yue, et al.
Published: (2024)
by: Chang, Yue, et al.
Published: (2024)
Rethinking Scientific Summarization Evaluation: Grounding Explainable Metrics on Facet-aware Benchmark
by: Chen, Xiuying, et al.
Published: (2024)
by: Chen, Xiuying, et al.
Published: (2024)
Fine-Grained Self-Endorsement Improves Factuality and Reasoning
by: Wang, Ante, et al.
Published: (2024)
by: Wang, Ante, et al.
Published: (2024)
Evaluate Summarization in Fine-Granularity: Auto Evaluation with LLM
by: Yuan, Dong, et al.
Published: (2024)
by: Yuan, Dong, et al.
Published: (2024)
Improving Factual Consistency of News Summarization by Contrastive Preference Optimization
by: Feng, Huawen, et al.
Published: (2023)
by: Feng, Huawen, et al.
Published: (2023)
MDSEval: A Meta-Evaluation Benchmark for Multimodal Dialogue Summarization
by: Liu, Yinhong, et al.
Published: (2025)
by: Liu, Yinhong, et al.
Published: (2025)
SummExecEdit: A Factual Consistency Benchmark in Summarization with Executable Edits
by: Thorat, Onkar, et al.
Published: (2024)
by: Thorat, Onkar, et al.
Published: (2024)
UniSumEval: Towards Unified, Fine-Grained, Multi-Dimensional Summarization Evaluation for LLMs
by: Lee, Yuho, et al.
Published: (2024)
by: Lee, Yuho, et al.
Published: (2024)
Trustworthy Reasoning: Evaluating and Enhancing Factual Accuracy in LLM Intermediate Thought Processes
by: Jiao, Rui, et al.
Published: (2025)
by: Jiao, Rui, et al.
Published: (2025)
Stress Testing Factual Consistency Metrics for Long-Document Summarization
by: Mujahid, Zain Muhammad, et al.
Published: (2025)
by: Mujahid, Zain Muhammad, et al.
Published: (2025)
Enhancing Factuality through Consensus and Consistency in Summarization Using Minimum Bayes Risk Decoding
by: Soetedjo, Riza Setiawan, et al.
Published: (2026)
by: Soetedjo, Riza Setiawan, et al.
Published: (2026)
EmoMeta: A Multimodal Dataset for Fine-grained Emotion Classification in Chinese Metaphors
by: Lu, Xingyuan, et al.
Published: (2025)
by: Lu, Xingyuan, et al.
Published: (2025)
Multimodal Dialog Systems with Dual Knowledge-enhanced Generative Pretrained Language Model
by: Chen, Xiaolin, et al.
Published: (2022)
by: Chen, Xiaolin, et al.
Published: (2022)
SEval-Ex: A Statement-Level Framework for Explainable Summarization Evaluation
by: Herserant, Tanguy, et al.
Published: (2025)
by: Herserant, Tanguy, et al.
Published: (2025)
APPLS: Evaluating Evaluation Metrics for Plain Language Summarization
by: Guo, Yue, et al.
Published: (2023)
by: Guo, Yue, et al.
Published: (2023)
SYNFAC-EDIT: Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization
by: Mishra, Prakamya, et al.
Published: (2024)
by: Mishra, Prakamya, et al.
Published: (2024)
Improving Factual Error Correction for Abstractive Summarization via Data Distillation and Conditional-generation Cloze
by: Li, Yiyang, et al.
Published: (2024)
by: Li, Yiyang, et al.
Published: (2024)
Similar Items
-
FineSurE: Fine-grained Summarization Evaluation using LLMs
by: Song, Hwanjun, et al.
Published: (2024) -
Improving Model Factuality with Fine-grained Critique-based Evaluator
by: Xie, Yiqing, et al.
Published: (2024) -
FGAIF: Aligning Large Vision-Language Models with Fine-grained AI Feedback
by: Jing, Liqiang, et al.
Published: (2024) -
PlainQAFact: Retrieval-augmented Factual Consistency Evaluation Metric for Biomedical Plain Language Summarization
by: You, Zhiwen, et al.
Published: (2025) -
QAPyramid: Fine-grained Evaluation of Content Selection for Text Summarization
by: Zhang, Shiyue, et al.
Published: (2024)