19 citations · 43 across the 24 of their papers we have counts for
10 papers · 1 filter
When to Think and When to Look: Uncertainty-Guided Lookback
Jing Bi, Filippos Bellos, Junjia Guo +8
Test-time thinking (that is, generating explicit intermediate reasoning chains) is known to boost performance in large language models and has recently shown strong gains for large…
Can Sound Replace Vision in LLaVA With Token Substitution?
Ali Vosoughi, Jing Bi, Pinxin Liu +2
What happens when we push audio-visual alignment to its absolute limits? To systematically investigate this question, we needed datasets with granular alignment quality annotations…
ZeroSep: Separate Anything in Audio with Zero Training
Chao Huang, Yuesheng Ma, Junxuan Huang +6
Audio source separation is fundamental for machines to understand complex acoustic environments and underpins numerous audio applications. Current supervised deep learning approach…
FreSca: Scaling in Frequency Space Enhances Diffusion Models
Chao Huang, Susan Liang, Yunlong Tang +4
Latent diffusion models (LDMs) have achieved remarkable success in a variety of image tasks, yet achieving fine-grained, disentangled control over global structures versus fine det…
MMPerspective: Do MLLMs Understand Perspective? A Comprehensive Benchmark for Perspective Perception, Reasoning, and Robustness
Yolo Y. Tang, Pinxin Liu, Zhangyun Tan +11
Understanding perspective is fundamental to human visual perception, yet the extent to which multimodal large language models (MLLMs) internalize perspective geometry remains uncle…
Caption Anything in Video: Fine-grained Object-centric Captioning via Spatiotemporal Multimodal Prompting
Yunlong Tang, Jing Bi, Chao Huang +16
We present CAT-V (Caption AnyThing in Video), a training-free framework for fine-grained object-centric video captioning that enables detailed descriptions of user-selected objects…
Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
Jiani Liu, Zhiyuan Wang, Zeliang Zhang +4
Vision Transformers (ViTs) have demonstrated impressive performance across a range of applications, including many safety-critical tasks. However, their unique architectural proper…
Why Reasoning Matters? A Survey of Advancements in Multimodal Reasoning (v1)
Jing Bi, Susan Liang, Xiaofei Zhou +16
Reasoning is central to human intelligence, enabling structured problem-solving across diverse tasks. Recent advances in large language models (LLMs) have greatly enhanced their re…
VERIFY: A Benchmark of Visual Explanation and Reasoning for Investigating Multimodal Reasoning Fidelity
Jing Bi, Junjia Guo, Susan Liang +8
Visual reasoning is central to human cognition, enabling individuals to interpret and abstractly understand their environment. Although recent Multimodal Large Language Models (MLL…
Generative AI for Cel-Animation: A Survey
Yolo Y. Tang, Junjia Guo, Pinxin Liu +14
Traditional Celluloid (Cel) Animation production pipeline encompasses multiple essential steps, including storyboarding, layout design, keyframe animation, inbetweening, and colori…