Papers with content quality
CharPoet: A Chinese Classical Poetry Generation System Based on Token-free LLM (2024.acl-demos)
Copied to clipboard
| Challenge: | Traditional systems in this field usually accept keywords as user inputs, resulting in limited control over content. |
| Approach: | They propose a Chinese classical poetry generation system based on token-free LLMs that allow unrestricted user instructions to be used. |
| Outcome: | The proposed system outperforms traditional systems including Jiuge and GPT-4 in format accuracy and content quality. |
Improved Near-Duplicate Detection for Aggregated and Paywalled News-Feeds (2025.naacl-industry)
Copied to clipboard
| Challenge: | News aggregators provide comprehensive and timely news stories that are sourced from diverse sources but differ in phrasing, formatting or supplemented with additional details. |
| Approach: | They propose a method that combines embeddings from pretrained language model and latent metadata of a news article followed by community detection to identify clusters of near-duplicates. |
| Outcome: | The proposed approach can detect nuanced similarities and differences in news snippets using pretrained language model and latent metadata of a news article followed by community detection. |
EmpDG: Multi-resolution Interactive Empathetic Dialogue Generation (2020.coling-main)
Copied to clipboard
| Challenge: | Existing work on empathetic dialogue generation fails to capture the nuances of human emotion and consider the potential of user feedback. |
| Approach: | They propose a multi-resolution adversarial model - EmpDG - to generate more empathetic responses by exploiting both coarse-grained dialogue-level and fine-grounded token-level emotions. |
| Outcome: | The proposed model outperforms the state-of-the-art models in both content quality and emotion perceptivity. |
FRAME: Feedback-Refined Agent Methodology for Enhancing Medical Research Insights (2025.findings-acl)
Copied to clipboard
| Challenge: | Existing approaches to automate scientific research are limited by human cognitive constraints and timeintensive workflows. |
| Approach: | They propose a framework that enhances medical paper generation through iterative refinement and structured feedback. |
| Outcome: | The proposed framework achieves significant improvements over conventional methods across multiple models and evaluation dimensions. |
ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcripts (2022.emnlp-main)
Copied to clipboard
Rajdeep Mukherjee, Abhinav Bohra, Akash Banerjee, Soumya Sharma, Manjunath Hegde, Afreen Shaikh, Shivani Shrivastava, Koustuv Dasgupta, Niloy Ganguly, Saptarshi Ghosh, Pawan Goyal
| Challenge: | ECTSum is a dataset for bullet-point summarization of earnings calls hosted by publicly traded companies. |
| Approach: | They propose a dataset with transcripts of earnings calls and bullet point summaries derived from Reuters articles. |
| Outcome: | The proposed dataset compares transcripts of earnings calls hosted by publicly traded companies with experts-written bullet point summaries derived from Reuters articles . |
UniCreative: Unifying Long-form Logic and Short-form Sparkle via Reference-Free Reinforcement Learning (2026.findings-acl)
Copied to clipboard
Xiaolong Wei, Zerun Zhu, Simin Niu, Xingyu Zhang, Peiying Yu, Changxuan Xiao, Yuchen Li, Jicheng Yang, Zhejun Zhao, Chong Meng, Long Xia, Daiting Shi
| Challenge: | Existing alignment paradigms for creative writing use static reward signals and supervised data. |
| Approach: | They propose a constraint-aware reward model that synthesizes query-specific criteria to provide fine-grained preference judgments. |
| Outcome: | The proposed framework aligns models with human preferences across content quality and structural paradigms without supervised fine-tuning and ground-truth references. |