Saved in:
| Main Authors: | Flores, Lorenzo Jaime Yu, Cohan, Arman |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.05788 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
Fine-Grained Self-Endorsement Improves Factuality and Reasoning
by: Wang, Ante, et al.
Published: (2024)
by: Wang, Ante, et al.
Published: (2024)
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)
On Evaluating LLM Alignment by Evaluating LLMs as Judges
by: Liu, Yixin, et al.
Published: (2025)
by: Liu, Yixin, et al.
Published: (2025)
Bayesian Calibration of Win Rate Estimation with LLM Evaluators
by: Gao, Yicheng, et al.
Published: (2024)
by: Gao, Yicheng, et al.
Published: (2024)
SUCEA: Reasoning-Intensive Retrieval for Adversarial Fact-checking through Claim Decomposition and Editing
by: Liu, Hongjun, et al.
Published: (2025)
by: Liu, Hongjun, et al.
Published: (2025)
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 Consistency of News Summarization by Contrastive Preference Optimization
by: Feng, Huawen, et al.
Published: (2023)
by: Feng, Huawen, et al.
Published: (2023)
Investigating Text Shortening Strategy in BERT: Truncation vs Summarization
by: Mutasodirin, Mirza Alim, et al.
Published: (2024)
by: Mutasodirin, Mirza Alim, et al.
Published: (2024)
IRIS: Interactive Research Ideation System for Accelerating Scientific Discovery
by: Garikaparthi, Aniketh, et al.
Published: (2025)
by: Garikaparthi, Aniketh, et al.
Published: (2025)
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 Legal Reasoning Traces with Legal Issue Tree Rubrics
by: Lee, Jinu, et al.
Published: (2025)
by: Lee, Jinu, et al.
Published: (2025)
Investigating Data Contamination in Modern Benchmarks for Large Language Models
by: Deng, Chunyuan, et al.
Published: (2023)
by: Deng, Chunyuan, et al.
Published: (2023)
M3SciQA: A Multi-Modal Multi-Document Scientific QA Benchmark for Evaluating Foundation Models
by: Li, Chuhan, et al.
Published: (2024)
by: Li, Chuhan, et al.
Published: (2024)
Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains
by: Ramprasad, Sanjana, et al.
Published: (2024)
by: Ramprasad, Sanjana, et al.
Published: (2024)
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)
AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research
by: Zhao, Yilun, et al.
Published: (2025)
by: Zhao, Yilun, et al.
Published: (2025)
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)
Calibrating Long-form Generations from Large Language Models
by: Huang, Yukun, et al.
Published: (2024)
by: Huang, Yukun, et al.
Published: (2024)
MIR: Methodology Inspiration Retrieval for Scientific Research Problems
by: Garikaparthi, Aniketh, et al.
Published: (2025)
by: Garikaparthi, Aniketh, et al.
Published: (2025)
When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets
by: Weller, Orion, et al.
Published: (2023)
by: Weller, Orion, et al.
Published: (2023)
RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation
by: Wu, Sihong, et al.
Published: (2026)
by: Wu, Sihong, et al.
Published: (2026)
COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences
by: Liu, Yixin, et al.
Published: (2024)
by: Liu, Yixin, et al.
Published: (2024)
MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise
by: Deng, Chunyuan, et al.
Published: (2024)
by: Deng, Chunyuan, et al.
Published: (2024)
FineSurE: Fine-grained Summarization Evaluation using LLMs
by: Song, Hwanjun, et al.
Published: (2024)
by: Song, Hwanjun, et al.
Published: (2024)
Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future
by: Wu, Sihong, et al.
Published: (2026)
by: Wu, Sihong, et al.
Published: (2026)
Advantages of Domain Knowledge Injection for Legal Document Summarization: A Case Study on Summarizing Indian Court Judgments in English and Hindi
by: Datta, Debtanu, et al.
Published: (2026)
by: Datta, Debtanu, et al.
Published: (2026)
Parameter-Efficient Fine-Tuning for Medical Text Summarization: A Comparative Study of Lora, Prompt Tuning, and Full Fine-Tuning
by: Shernazarov, Ulugbek, et al.
Published: (2026)
by: Shernazarov, Ulugbek, et al.
Published: (2026)
Factuality on Demand: Controlling the Factuality-Informativeness Trade-off in Text Generation
by: Gong, Ziwei, et al.
Published: (2026)
by: Gong, Ziwei, et al.
Published: (2026)
Improving the Calibration of Confidence Scores in Text Generation Using the Output Distribution's Characteristics
by: Flores, Lorenzo Jaime Yu, et al.
Published: (2025)
by: Flores, Lorenzo Jaime Yu, et al.
Published: (2025)
Re-evaluating Automatic LLM System Ranking for Alignment with Human Preference
by: Gao, Mingqi, et al.
Published: (2024)
by: Gao, Mingqi, et al.
Published: (2024)
From Scores to Steps: Diagnosing and Improving LLM Performance in Evidence-Based Medical Calculations
by: Wang, Benlu, et al.
Published: (2025)
by: Wang, Benlu, et al.
Published: (2025)
Evaluate Summarization in Fine-Granularity: Auto Evaluation with LLM
by: Yuan, Dong, et al.
Published: (2024)
by: Yuan, Dong, et al.
Published: (2024)
FG-RAG: Enhancing Query-Focused Summarization with Context-Aware Fine-Grained Graph RAG
by: Hong, Yubin, et al.
Published: (2025)
by: Hong, Yubin, et al.
Published: (2025)
SciMDR: Advancing Scientific Multimodal Document Reasoning
by: Chen, Ziyu, et al.
Published: (2026)
by: Chen, Ziyu, et al.
Published: (2026)
MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning
by: Tang, Xiangru, et al.
Published: (2023)
by: Tang, Xiangru, et al.
Published: (2023)
Do Automatic Factuality Metrics Measure Factuality? A Critical Evaluation
by: Ramprasad, Sanjana, et al.
Published: (2024)
by: Ramprasad, Sanjana, et al.
Published: (2024)
References Improve LLM Alignment in Non-Verifiable Domains
by: Shi, Kejian, et al.
Published: (2026)
by: Shi, Kejian, et al.
Published: (2026)
QAPyramid: Fine-grained Evaluation of Content Selection for Text Summarization
by: Zhang, Shiyue, et al.
Published: (2024)
by: Zhang, Shiyue, et al.
Published: (2024)
Fine-Tuned Language Models for Domain-Specific Summarization and Tagging
by: Wang, Jun, et al.
Published: (2025)
by: Wang, Jun, et al.
Published: (2025)
Similar Items
-
ReFEree: Reference-Free and Fine-Grained Method for Evaluating Factual Consistency in Real-World Code Summarization
by: Bae, Suyoung, et al.
Published: (2026) -
Fine-Grained Self-Endorsement Improves Factuality and Reasoning
by: Wang, Ante, et al.
Published: (2024) -
Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models
by: Song, Jongyoon, et al.
Published: (2024) -
On Evaluating LLM Alignment by Evaluating LLMs as Judges
by: Liu, Yixin, et al.
Published: (2025) -
Bayesian Calibration of Win Rate Estimation with LLM Evaluators
by: Gao, Yicheng, et al.
Published: (2024)