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20232026
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7 papers · 1 filter

cs.CV2025

DocSLM: A Small Vision-Language Model for Long Multimodal Document Understanding

Tanveer Hannan, Dimitrios Mallios, Parth Pathak +5

Large Vision-Language Models (LVLMs) have demonstrated strong multimodal reasoning capabilities on long and complex documents. However, their high memory footprint makes them impra…

cs.CL2025

PRSM: A Measure to Evaluate CLIP's Robustness Against Paraphrases

Udo Schlegel, Franziska Weeber, Jian Lan +1

Contrastive Language-Image Pre-training (CLIP) is a widely used multimodal model that aligns text and image representations through large-scale training. While it performs strongly…

cs.CV2025

Human Uncertainty-Aware Data Selection and Automatic Labeling in Visual Question Answering

Jian Lan, Zhicheng Liu, Udo Schlegel +5

Large vision-language models (VLMs) achieve strong performance in Visual Question Answering but still rely heavily on supervised fine-tuning (SFT) with massive labeled datasets, wh…

cs.CV2025

SVAG-Bench: A Large-Scale Benchmark for Multi-Instance Spatio-temporal Video Action Grounding

Tanveer Hannan, Shuaicong Wu, Mark Weber +6

A truly capable AI system must do more than detect objects or recognize activities in isolation. It must form unified, grounded representations of who is acting, what they are doin…

cs.CL2025

Enhancing Robustness of Autoregressive Language Models against Orthographic Attacks via Pixel-based Approach

Han Yang, Jian Lan, Yihong Liu +2

Autoregressive language models are vulnerable to orthographic attacks, where input text is perturbed with characters from multilingual alphabets, leading to substantial performance…

cs.CV2025

AViLA: Asynchronous Vision-Language Agent for Streaming Multimodal Data Interaction

Gengyuan Zhang, Tanveer Hannan, Hermine Kleiner +6

An ideal vision-language agent serves as a bridge between the human users and their surrounding physical world in real-world applications like autonomous driving and embodied agent…

cs.CL2025

Unveiling the "Fairness Seesaw": Discovering and Mitigating Gender and Race Bias in Vision-Language Models

Jian Lan, Udo Schlegel, Tanveer Hannan +3

Although Vision-Language Models (VLMs) have achieved remarkable success, the knowledge mechanisms underlying their social biases remain a black box, where fairness- and ethics-rela…