arXiv:1903.00384
공식 코드 · Papers with Code
Data-driven Approach for Quality Evaluation on Knowledge Sharing Platform
원문 초록
In recent years, voice knowledge sharing and question answering (Q&A) platforms have attracted much attention, which greatly facilitate the knowledge acquisition for people. However, little research has evaluated on the quality evaluation on voice knowledge sharing. This paper presents a data-driven approach to automatically evaluate the quality of a specific Q&A platform (Zhihu Live). Extensive experiments demonstrate the effectiveness of the proposed method. Furthermore, we introduce a dataset of Zhihu Live as an open resource for researchers in related areas. This dataset will facilitate the development of new methods on knowledge sharing services quality evaluation.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
From Roots to Rewards: Dynamic Tree Reasoning with RL
Describe Anything Model for Visual Question Answering on Text-rich Images
Warehouse Spatial Question Answering with LLM Agent
L0: Reinforcement Learning to Become General Agents
Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder
Revisiting CroPA: A Reproducibility Study and Enhancements for Cross-Prompt Adversarial Transferability in Vision-Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.