13 citations · 20 across the 7 of their papers we have counts for
8 papers
Where MLLMs Fail and Why: Causal Task Decomposition for Capability Failure Diagnosis
Xia Hu, Brian Potetz, Chun-Ta Lu +6
End-to-end accuracy on compositional tasks records how often MLLMs fail, but cannot distinguish whether a failure reflects an intrinsic deficit in the targeted capability or a casc…
The Cartesian Shortcut: Re-evaluate Vision Reasoning in Polar Coordinate Space
Xia Hu, Zhenrui Yue, Brian Potetz +4
As current Multimodal Large Language Models rapidly saturate canonical visual reasoning benchmarks, a key question emerges: do these strong scores genuinely reflect robust visual u…
Agile Deliberation: Concept Deliberation for Subjective Visual Classification
Leijie Wang, Otilia Stretcu, Wei Qiao +7
From content moderation to content curation, applications requiring vision classifiers for visual concepts are rapidly expanding. Existing human-in-the-loop approaches typically as…
S2Vec: Self-Supervised Geospatial Embeddings for the Built Environment
Shushman Choudhury, Elad Aharoni, Chandrakumari Suvarna +4
Scalable general-purpose representations of the built environment are crucial for geospatial artificial intelligence applications. This paper introduces S2Vec, a novel self-supervi…
Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use
Imad Eddine Toubal, Aditya Avinash, Neil Gordon Alldrin +10
From content moderation to wildlife conservation, the number of applications that require models to recognize nuanced or subjective visual concepts is growing. Traditionally, devel…
Scaling Up LLM Reviews for Google Ads Content Moderation
Wei Qiao, Tushar Dogra, Otilia Stretcu +11
Large language models (LLMs) are powerful tools for content moderation, but their inference costs and latency make them prohibitive for casual use on large datasets, such as the Go…
Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models
Yushi Hu, Otilia Stretcu, Chun-Ta Lu +5
Solving complex visual tasks such as "Who invented the musical instrument on the right?" involves a composition of skills: understanding space, recognizing instruments, and also re…
Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling
Yaqing Wang, Jialin Wu, Tanmaya Dabral +8
Large language models (LLMs) and vision language models (VLMs) demonstrate excellent performance on a wide range of tasks by scaling up parameter counts from O(10^9) to O(10^{12})…