Dialog policy optimization for low resource setting using Self-play and Reward based Sampling

no code implementations • PACLIC 2020 • Tharindu Madusanka, Durashi Langappuli, Thisara Welmilla, Uthayasanker Thayasivam, Sanath Jayasena

Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluation

no code implementations • 5 Jun 2024 • Hao Li, Yuping Wu, Viktor Schlegel, Riza Batista-Navarro, Tharindu Madusanka, Iqra Zahid, Jiayan Zeng, Xiaochi Wang, Xinran He, Yizhi Li, Goran Nenadic

In our work, we introduce an argument mining dataset that captures the end-to-end process of preparing an argumentative essay for a debate, which covers the tasks of claim and evidence identification (Task 1 ED), evidence convincingness ranking (Task 2 ECR), argumentative essay summarisation and human preference ranking (Task 3 ASR) and metric learning for automated evaluation of resulting essays, based on human feedback along argument quality dimensions (Task 4 SQE).

Argument Mining Metric Learning +1