Education
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Learning modular object-centric representations is crucial for systematic generalization.
CALVIN: Improved Contextual Video Captioning via Instruction Tuning
The recent emergence of powerful Vision-Language models (VLMs) has significantly improved image captioning.
CausalChaos for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes
Understanding the intricate motivations behind human actions is paramount in developing sophisticated systems capable of nuanced behavior analysis.
a8808b75b299d64a23255bc8d30fb786-Paper-Conference.pdf
Can a physicist make only a finite number of errors in the eternal quest to uncover the law of nature? This millennium-old philosophical problem, known as inductive inference, lies at the heart of epistemology.
ConStat: Performance-Based Contamination Detection in Large Language Models Jasper Dekoninck 1, Mark Niklas Müller 1,2, Martin Vechev 1 Department of Computer Science 1
Public benchmarks play an essential role in the evaluation of large language models.
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels
However, these methods typically rely on strict assumptions and are limited to certain types of label noise. In this paper, we reformulate the label-noise problem from a generative-model perspective, i.e., labels are generated by gradually refining an initial random guess.
