activity
20242026
most citedOn the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective

1 citations · 1 across the 4 of their papers we have counts for

collaborators
Showing 2025Show all

8 papers · 1 filter

cs.CV2025

GenEval 2: Addressing Benchmark Drift in Text-to-Image Evaluation

Amita Kamath, Kai-Wei Chang, Ranjay Krishna +3

Automating Text-to-Image (T2I) model evaluation is challenging; a judge model must be used to score correctness, and test prompts must be selected to be challenging for current T2I…

cs.CV2025

Structure From Tracking: Distilling Structure-Preserving Motion for Video Generation

Yang Fei, George Stoica, Jingyuan Liu +4

Reality is a dance between rigid constraints and deformable structures. For video models, that means generating motion that preserves fidelity as well as structure. Despite progres…

cs.CV2025

Visual Representations inside the Language Model

Benlin Liu, Amita Kamath, Madeleine Grunde-McLaughlin +2

Despite interpretability work analyzing VIT encoders and transformer activations, we don't yet understand why Multimodal Language Models (MLMs) struggle on perception-heavy tasks.…

cs.CV2025

Reinforced Visual Perception with Tools

Zetong Zhou, Dongping Chen, Zixian Ma +6

Visual reasoning, a cornerstone of human intelligence, encompasses complex perceptual and logical processes essential for solving diverse visual problems. While advances in compute…

cs.CV2025

MultiRef: Controllable Image Generation with Multiple Visual References

Ruoxi Chen, Dongping Chen, Siyuan Wu +6

Visual designers naturally draw inspiration from multiple visual references, combining diverse elements and aesthetic principles to create artwork. However, current image generativ…

cs.CV2025

RefTok: Reference-Based Tokenization for Video Generation

Xiang Fan, Xiaohang Sun, Kushan Thakkar +4

Effectively handling temporal redundancy remains a key challenge in learning video models. Prevailing approaches often treat each set of frames independently, failing to effectivel…