8 citations · 10 across the 5 of their papers we have counts for
5 papers
CLINB: A Climate Intelligence Benchmark for Foundational Models
Michelle Chen Huebscher, Katharine Mach, Aleksandar Stanić +10
Evaluating how Large Language Models (LLMs) handle complex, specialized knowledge remains a critical challenge. We address this through the lens of climate change by introducing CL…
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery
Anand Gopalakrishnan, Aleksandar Stanić, Jürgen Schmidhuber +1
Current state-of-the-art synchrony-based models encode object bindings with complex-valued activations and compute with real-valued weights in feedforward architectures. We argue f…
Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers
Aleksandar Stanić, Sergi Caelles, Michael Tschannen
Visual reasoning is dominated by end-to-end neural networks scaled to billions of model parameters and training examples. However, even the largest models struggle with composition…
Mindstorms in Natural Language-Based Societies of Mind
Mingchen Zhuge, Haozhe Liu, Francesco Faccio +23
Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each o…
Contrastive Training of Complex-Valued Autoencoders for Object Discovery
Aleksandar Stanić, Anand Gopalakrishnan, Kazuki Irie +1
Current state-of-the-art object-centric models use slots and attention-based routing for binding. However, this class of models has several conceptual limitations: the number of sl…