activity
20222025
most citedInteractive Natural Language Processing

23 citations · 77 across the 43 of their papers we have counts for

collaborators
Showing cs.CLShow all

35 papers · 1 filter

cs.CL2025

Who's Laughing Now? An Overview of Computational Humour Generation and Explanation

Tyler Loakman, William Thorne, Chenghua Lin

The creation and perception of humour is a fundamental human trait, positioning its computational understanding as one of the most challenging tasks in natural language processing…

cs.CL2025

EvolvTrip: Enhancing Literary Character Understanding with Temporal Theory-of-Mind Graphs

Bohao Yang, Hainiu Xu, Jinhua Du +3

A compelling portrayal of characters is essential to the success of narrative writing. For readers, appreciating a character's traits requires the ability to infer their evolving b…

cs.CL2025

Overview of the NLPCC 2025 Shared Task: Gender Bias Mitigation Challenge

Yizhi Li, Ge Zhang, Hanhua Hong +2

As natural language processing for gender bias becomes a significant interdisciplinary topic, the prevalent data-driven techniques, such as pre-trained language models, suffer from…

cs.CL2025

Selecting Demonstrations for Many-Shot In-Context Learning via Gradient Matching

Jianfei Zhang, Bei Li, Jun Bai +4

In-Context Learning (ICL) empowers Large Language Models (LLMs) for rapid task adaptation without Fine-Tuning (FT), but its reliance on demonstration selection remains a critical c…

cs.CL2025

DRE: An Effective Dual-Refined Method for Integrating Small and Large Language Models in Open-Domain Dialogue Evaluation

Kun Zhao, Bohao Yang, Chen Tang +4

Large Language Models (LLMs) excel at many tasks but struggle with ambiguous scenarios where multiple valid responses exist, often yielding unreliable results. Conversely, Small La…

cs.CL2025

COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values

P Team, Siwei Wu, Jincheng Ren +29

Aligning large language models (LLMs) with human preferences has achieved remarkable success. However, existing Chinese preference datasets are limited by small scale, narrow domai…