6 citations · 12 across the 8 of their papers we have counts for
5 papers · 1 filter
SpaceR: Reinforcing MLLMs in Video Spatial Reasoning
Kun Ouyang, Yuanxin Liu, Haoning Wu +5
Video spatial reasoning, which involves inferring the underlying spatial structure from observed video frames, poses a significant challenge for existing Multimodal Large Language…
VideoReasonBench: Can MLLMs Perform Vision-Centric Complex Video Reasoning?
Yuanxin Liu, Kun Ouyang, Haoning Wu +7
Recent studies have shown that long chain-of-thought (CoT) reasoning can significantly enhance the performance of large language models (LLMs) on complex tasks. However, this benef…
PunchBench: Benchmarking MLLMs in Multimodal Punchline Comprehension
Kun Ouyang, Yuanxin Liu, Shicheng Li +5
Multimodal punchlines, which involve humor or sarcasm conveyed in image-caption pairs, are a popular way of communication on online multimedia platforms. With the rapid development…
TempCompass: Do Video LLMs Really Understand Videos?
Yuanxin Liu, Shicheng Li, Yi Liu +6
Recently, there is a surge in interest surrounding video large language models (Video LLMs). However, existing benchmarks fail to provide a comprehensive feedback on the temporal p…
VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models
Shicheng Li, Lei Li, Shuhuai Ren +5
The ability to perceive how objects change over time is a crucial ingredient in human intelligence. However, current benchmarks cannot faithfully reflect the temporal understanding…