3 papers
cs.CL2026
SagaQA: A Multi-hop Reasoning Benchmark for Long-form Narrative Understanding in TV Series
Galann Pennec, Zhengyuan Liu, Nicholas Asher +2
We introduce SagaQA, a long-form video benchmark for multi-hop reasoning over full-length TV series. Existing video reasoning benchmarks often emphasize local understanding of adja…
cs.CL2026
Minimal Clips, Maximum Salience: Long Video Summarization via Key Moment Extraction
Galann Pennec, Zhengyuan Liu, Nicholas Asher +2
Vision-Language Models (VLMs) are able to process increasingly longer videos. Yet, important visual information is easily lost throughout the entire context and missed by VLMs. Als…
cs.CL2025
Integrating Video and Text: A Balanced Approach to Multimodal Summary Generation and Evaluation
Galann Pennec, Zhengyuan Liu, Nicholas Asher +2
Vision-Language Models (VLMs) often struggle to balance visual and textual information when summarizing complex multimodal inputs, such as entire TV show episodes. In this paper, w…