3 accepted papers
Traditional methods for processing classical Chinese typically segment language understanding into discrete tasks, which overlook crucial background information and reduce user engagement. Large language models (LLMs) provide integrated solutions, yet they entail high computational costs and risks o…
Given the importance of ancient Chinese in capturing the essence of rich historical and cultural heritage, the rapid advancements in Large Language Models (LLMs) necessitate benchmarks that can effectively evaluate their understanding of ancient contexts. To meet this need, we present AC-EVAL, an in…
Video Question Answering (VideoQA) tasks require not only correct answers but also visual evidence. The “localize-then-answer” strategy, while enhancing accuracy and interpretability, faces challenges due to the lack of temporal localization labels in VideoQA datasets. Existing methods often train t…