5 accepted papers
Large Reason Models (LRMs) extend long reasoning process to solve complex tasks. However, due to the lack of fine-grained control, they often suffer from overthinking and erroneous reasoning problems, risking accuracy loss. To address this issue, we introduce Reasoning Direction Steering (RDS) to en
Community-based Question Answering (CQA) summarization aims to generate a summary from a collection of QA pairs about a specific entity. Unlike well-structured texts such as dialogues, a set of QA pairs often contains significant redundancy, including repetitive questions and similar answers. The ab…
Large Language Models (LLMs) have achieved impressive results in Machine Translation by simply following instructions, even without training on parallel data. However, LLMs still face challenges on low-resource languages due to the lack of pre-training data. In real-world situations, humans can beco…
Maintaining faithfulness between responses and knowledge is an important research topic for building reliable knowledge-grounded dialogue systems. Existing models heavily rely on elaborate data engineering or increasing the model’s parameters ignoring to track the tokens that significantly influence…
Intention, emotion and action are important elements in human activities. Modeling the interaction process between individuals by analyzing the relationships between these elements is a challenging task. However, previous work mainly focused on modeling intention and emotion independently, and negle…