9 citations · 14 across the 3 of their papers we have counts for
5 papers · 1 filter
NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning
Wei Liu, Siya Qi, Xinyu Wang +3
Recent advances such as DeepSeek R1-Zero highlight the effectiveness of incentive training, a reinforcement learning paradigm that computes rewards solely based on the final answer…
CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization
Wei Liu, Huanqin Wu, Wenjing Mu +3
Generating factual-consistent summaries is a challenging task for abstractive summarization. Previous works mainly encode factual information or perform post-correct/rank after dec…
Subjective Bias in Abstractive Summarization
Lei Li, Wei Liu, Marina Litvak +4
Due to the subjectivity of the summarization, it is a good practice to have more than one gold summary for each training document. However, many modern large-scale abstractive summ…
UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Prediction
Huanqin Wu, Wei Liu, Lei Li +4
Keyphrase Prediction (KP) task aims at predicting several keyphrases that can summarize the main idea of the given document. Mainstream KP methods can be categorized into purely ge…
In Conclusion Not Repetition: Comprehensive Abstractive Summarization With Diversified Attention Based On Determinantal Point Processes
Lei Li, Wei Liu, Marina Litvak +2
Various Seq2Seq learning models designed for machine translation were applied for abstractive summarization task recently. Despite these models provide high ROUGE scores, they are…