Multi-Perspective Transformers in ARC-AGI-2 Challenge

2026-05-01 · Caleb Talley, Vedant Tibrewal, Seun Adekunle, Weiwen Dong, Xinyu Wu, Fariha Sheikh arxiv

ARC-AGI-2 is a benchmark of human-intuitive visual puzzles that measures a machine's ability to generalize from limited examples, interpret symbolic meaning, and flexibly apply rules in varying contexts. In this paper, we discuss our approach to solving the ARC-AGI-2 puzzles with TinyLM, with additional fine-tuning at test time, including Test-Time-Training (TTT) and Products of Experts (POE). Our model achieves 96.1% accuracy on the training set and 21.7% accuracy on the evaluation set.

📄 PDF Abstract BibTeX arXiv:2605.01154

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Transformers in Time Series: A Survey

2022-02-15 · Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen 외

Transformers have achieved superior performances in many tasks in natural language processing and computer vision, which also triggered great interest in the time series community. Among multiple advantages of Transforme…

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Speech Recognition Transformers: Topological-lingualism Perspective

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Transformers have evolved with great success in various artificial intelligence tasks. Thanks to our recent prevalence of self-attention mechanisms, which capture long-term dependency, phenomenal outcomes in speech proce…

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Transformers play a central role in the inner workings of large language models. We develop a mathematical framework for analyzing Transformers based on their interpretation as interacting particle systems, which reveals…

Graph Transformers: A Survey

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Graph transformers are a recent advancement in machine learning, offering a new class of neural network models for graph-structured data. The synergy between transformers and graph learning demonstrates strong performanc…

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Multimodal Learning with Transformers: A Survey

2022-06-13 · Peng Xu, Xiatian Zhu, David A. Clifton

Transformer is a promising neural network learner, and has achieved great success in various machine learning tasks. Thanks to the recent prevalence of multimodal applications and big data, Transformer-based multimodal l…

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