9 citations · 12 across the 5 of their papers we have counts for
6 papers
EpiCon: Collective Agent Learning through Co-Evolving Multimodal Memory
Ziyun Zeng, Hang Hua, Shaden Alshammari +3
Agents can learn from past executions, but enabling different agents to reuse and build on one another's experience remains challenging. We introduce EpiCon, a shared multimodal me…
MathNet: a Global Multimodal Benchmark for Mathematical Reasoning and Retrieval
Shaden Alshammari, Kevin Wen, Abrar Zainal +5
Mathematical problem solving remains a challenging test of reasoning for large language and multimodal models, yet existing benchmarks are limited in size, language coverage, and t…
Beyond I-Con: Exploring New Dimension of Distance Measures in Representation Learning
Jasmine Shone, Zhening Li, Shaden Alshammari +2
The Information Contrastive (I-Con) framework revealed that over 23 representation learning methods implicitly minimize KL divergence between data and learned distributions that en…
I-Con: A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann +2
As the field of representation learning grows, there has been a proliferation of different loss functions to solve different classes of problems. We introduce a single information-…
Vision-Language Models Do Not Understand Negation
Kumail Alhamoud, Shaden Alshammari, Yonglong Tian +4
Many practical vision-language applications require models that understand negation, e.g., when using natural language to retrieve images which contain certain objects but not othe…
Long-Tailed Recognition via Weight Balancing
Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan +1
In the real open world, data tends to follow long-tailed class distributions, motivating the well-studied long-tailed recognition (LTR) problem. Naive training produces models that…