39 citations · 60 across the 30 of their papers we have counts for
33 papers
VidHarness: Evolving Agent Harnesses for Cost-Efficient Long Video Understanding
Susan Liang, Jianmin Wu, Daxiang Dong
Vision-language models (VLMs) can answer questions about hour-long videos, but processing every frame is prohibitively expensive, even though the evidence for a question usually sp…
AdaTurn: Budget-Aware Test-Time Scaling for Active Visual Perception Agents
Susan Liang, Chao Huang, Filippos Bellos +3
Active visual agents solve fine-grained image tasks by interleaving reasoning with image-grounding actions across multiple turns. However, deployment-time rollout budgets are rarel…
SurgAtlas: A Large-Scale Surgical Video-Language Dataset with 2,391 Hours of Open and Minimally Invasive Surgery
Filippos Bellos, Andre S. Gala-Garza, Miaowei Wang +8
We introduce SurgAtlas, the largest surgical video-language dataset to date, comprising 15,291 videos (2,391 hours) spanning 18 surgical specialties and over 5,000 procedure types,…
Suppression Is Not Forgetting: Residual Recoverability in Visual Concept Unlearning for VLMs
Zhangyun Tan, Zeliang Zhang, Jiani Liu +5
Vision-language models (VLMs) may need to forget visual concepts after deployment because of privacy, copyright, licensing, safety, or policy changes. Conventional machine unlearni…
TDMM-LM: Bridging Facial Understanding and Animation via Language Models
Luchuan Song, Pinxin Liu, Haiyang Liu +7
Text-guided human body animation has advanced rapidly, yet facial animation lags due to the scarcity of well-annotated, text-paired facial corpora. To close this gap, we leverage f…
Omni-Judge: Can Omni-LLMs Serve as Human-Aligned Judges for Text-Conditioned Audio-Video Generation?
Susan Liang, Chao Huang, Filippos Bellos +7
State-of-the-art text-to-video generation models such as Sora 2 and Veo 3 can now produce high-fidelity videos with synchronized audio directly from a textual prompt, marking a new…
Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models
Yolo Y. Tang, Jing Bi, Pinxin Liu +24
Video understanding represents the most challenging frontier in computer vision, requiring models to reason about complex spatiotemporal relationships, long-term dependencies, and…
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…
High-Quality Sound Separation Across Diverse Categories via Visually-Guided Generative Modeling
Chao Huang, Susan Liang, Yapeng Tian +2
We propose DAVIS, a Diffusion-based Audio-VIsual Separation framework that solves the audio-visual sound source separation task through generative learning. Existing methods typica…
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…
BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
Susan Liang, Dejan Markovic, Israel D. Gebru +7
Binaural rendering aims to synthesize binaural audio that mimics natural hearing based on a mono audio and the locations of the speaker and listener. Although many methods have bee…
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…
CalibQuant: 1-Bit KV Cache Quantization for Multimodal LLMs
Insu Han, Zeliang Zhang, Zhiyuan Wang +8
Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance across diverse applications. However, their computational overhead during deployment remains a cri…
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…
Rethinking Audio-Visual Adversarial Vulnerability from Temporal and Modality Perspectives
Zeliang Zhang, Susan Liang, Daiki Shimada +1
While audio-visual learning equips models with a richer understanding of the real world by leveraging multiple sensory modalities, this integration also introduces new vulnerabilit…
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…
Language-Guided Joint Audio-Visual Editing via One-Shot Adaptation
Susan Liang, Chao Huang, Yapeng Tian +2
In this paper, we introduce a novel task called language-guided joint audio-visual editing. Given an audio and image pair of a sounding event, this task aims at generating new audi…
VidComposition: Can MLLMs Analyze Compositions in Compiled Videos?
Yolo Y. Tang, Junjia Guo, Hang Hua +9
The advancement of Multimodal Large Language Models (MLLMs) has enabled significant progress in multimodal understanding, expanding their capacity to analyze video content. However…
Scaling Concept With Text-Guided Diffusion Models
Chao Huang, Susan Liang, Yunlong Tang +3
Text-guided diffusion models have revolutionized generative tasks by producing high-fidelity content from text descriptions. They have also enabled an editing paradigm where concep…
Will the Inclusion of Generated Data Amplify Bias Across Generations in Future Image Classification Models?
Zeliang Zhang, Xin Liang, Mingqian Feng +2
As the demand for high-quality training data escalates, researchers have increasingly turned to generative models to create synthetic data, addressing data scarcity and enabling co…