14 papers
VisualOverload: Probing Visual Understanding of VLMs in Really Dense Scenes
Paul Gavrikov, Wei Lin, M. Jehanzeb Mirza +6
Is basic visual understanding really solved in state-of-the-art VLMs? We present VisualOverload, a slightly different visual question answering (VQA) benchmark comprising 2,720 que…
AVRT: Audio-Visual Reasoning Transfer through Single-Modality Teachers
Edson Araujo, Saurabhchand Bhati, M. Jehanzeb Mirza +5
Recent advances in reasoning models have shown remarkable progress in text-based domains, but transferring those capabilities to multimodal settings, e.g., to allow reasoning over…
TTA-Vid: Generalized Test-Time Adaptation for Video Reasoning
Soumya Shamarao Jahagirdar, Edson Araujo, Anna Kukleva +7
Recent video reasoning models have shown strong results on temporal and multimodal understanding, yet they depend on large-scale supervised data and multi-stage training pipelines,…
PRISMM-Bench: A Benchmark of Peer-Review Grounded Multimodal Inconsistencies
Lukas Selch, Yufang Hou, M. Jehanzeb Mirza +4
Large Multimodal Models (LMMs) are increasingly applied to scientific research, yet it remains unclear whether they can reliably understand and reason over the multimodal complexit…
TTRV: Test-Time Reinforcement Learning for Vision Language Models
Akshit Singh, Shyam Marjit, Wei Lin +7
Existing methods for extracting reward signals in Reinforcement Learning typically rely on labeled data and dedicated training splits, a setup that contrasts with how humans learn…
Towards Audio Token Compression in Large Audio Language Models
Saurabhchand Bhati, Samuel Thomas, Hilde Kuehne +2
Large Audio Language Models (LALMs) deliver strong performance across speech and audio tasks, but their audio encoders generate high-rate token sequences (e.g., 25 tokens/s), makin…