5 papers
ENTER: Event Based Interpretable Reasoning for VideoQA
Hammad Ayyubi, Junzhang Liu, Ali Asgarov +10
In this paper, we present ENTER, an interpretable Video Question Answering (VideoQA) system based on event graphs. Event graphs convert videos into graphical representations, where…
Detecting Multimodal Situations with Insufficient Context and Abstaining from Baseless Predictions
Junzhang Liu, Zhecan Wang, Hammad Ayyubi +5
Despite the widespread adoption of Vision-Language Understanding (VLU) benchmarks such as VQA v2, OKVQA, A-OKVQA, GQA, VCR, SWAG, and VisualCOMET, our analysis reveals a pervasive…
PuzzleGPT: Emulating Human Puzzle-Solving Ability for Time and Location Prediction
Hammad Ayyubi, Xuande Feng, Junzhang Liu +3
The task of predicting time and location from images is challenging and requires complex human-like puzzle-solving ability over different clues. In this work, we formalize this abi…
JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images
Zhecan Wang, Junzhang Liu, Chia-Wei Tang +11
Existing vision-language understanding benchmarks largely consist of images of objects in their usual contexts. As a consequence, recent multimodal large language models can perfor…
ElastiFormer: Learned Redundancy Reduction in Transformer via Self-Distillation
Junzhang Liu, Tingkai Liu, Yueyuan Sui +1
We introduce ElastiFormer, a post-training technique that adapts pretrained Transformer models into an elastic counterpart with variable inference time compute. ElastiFormer introd…