2 citations · 2 across the 4 of their papers we have counts for
5 papers
Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering
Zizhen Wang, Bo Feng, Zhengfeng Lai +5
Evaluating video captioning remains a critical challenge for Visual Large Language Models (VLLMs). Existing metrics primarily rely on matching generated text against ground-truth r…
MedAction: Towards Active Multi-turn Clinical Diagnostic LLMs
Hsin-Ling Hsu, Zizheng Wang, Donghua Zhang +9
Most existing LLM diagnoses are evaluated on static, single-turn settings where complete patient information is provided upfront, an oversimplification of real clinical practice. W…
Kimi K2.5: Visual Agentic Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +333
We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…
SeqBench: Benchmarking Sequential Narrative Generation in Text-to-Video Models
Zhengxu Tang, Zizheng Wang, Luning Wang +8
Text-to-video (T2V) generation models have made significant progress in creating visually appealing videos. However, they struggle with generating coherent sequential narratives th…
Breaking Down Video LLM Benchmarks: Knowledge, Spatial Perception, or True Temporal Understanding?
Bo Feng, Zhengfeng Lai, Shiyu Li +4
Existing video understanding benchmarks often conflate knowledge-based and purely image-based questions, rather than clearly isolating a model's temporal reasoning ability, which i…