collaborators

6 papers

cs.CV2026

Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation

Tobia Poppi, Silvia Cappelletti, Sara Sarto +5

Recent progress in generative modeling has made safety control a central challenge, yet existing approaches remain largely model-specific, requiring retraining or tailored interven…

cs.CV2026

Learning to Rank Caption Chains for Video-Text Alignment

Ansel Blume, Burak Uzkent, Shalini Chaudhuri +1

Direct preference optimization (DPO) is an effective technique to train language models to generate preferred over dispreferred responses. However, this binary "winner-takes-all" a…

cs.CV2026

Narrative Aligned Long Form Video Question Answering

Rahul Jain, Keval Doshi, Burak Uzkent +1

Recent progress in multimodal large language models (MLLMs) has led to a surge of benchmarks for long-video reasoning. However, most existing benchmarks rely on localized cues and…

cs.CV2026

Perceptio: Perception Enhanced Vision Language Models via Spatial Token Generation

Yuchen Li, Amanmeet Garg, Shalini Chaudhuri +2

Large Vision Language Models (LVLMs) excel at semantic understanding but struggle with fine grained spatial grounding, as the model must implicitly infer complex geometry without e…

cs.CV2026

CounterVid: Counterfactual Video Generation for Mitigating Action and Temporal Hallucinations in Video-Language Models

Tobia Poppi, Burak Uzkent, Amanmeet Garg +7

Video-language models (VLMs) achieve strong multimodal understanding but remain prone to hallucinations, especially when reasoning about actions and temporal order. Existing mitiga…

cs.CV2025

From Frames to Clips: Training-free Adaptive Key Clip Selection for Long-Form Video Understanding

Guangyu Sun, Archit Singhal, Burak Uzkent +3

Video Large Language Models (VLMs) have achieved strong performance on various vision-language tasks, yet their practical use is limited by the massive number of visual tokens prod…