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20202026
most citedPointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

418 citations · 578 across the 22 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.LG2023

From Categories to Classifiers: Name-Only Continual Learning by Exploring the Web

Ameya Prabhu, Hasan Abed Al Kader Hammoud, Ser-Nam Lim +3

Continual Learning (CL) often relies on the availability of extensive annotated datasets, an assumption that is unrealistically time-consuming and costly in practice. We explore a…

cs.LG2023★ 3 cited

Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right?

Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim +3

We revisit the common practice of evaluating adaptation of Online Continual Learning (OCL) algorithms through the metric of online accuracy, which measures the accuracy of the mode…

cs.AI2023★ 8 cited

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…

cs.LG2023

Real-Time Evaluation in Online Continual Learning: A New Hope

Yasir Ghunaim, Adel Bibi, Kumail Alhamoud +5

Current evaluations of Continual Learning (CL) methods typically assume that there is no constraint on training time and computation. This is an unrealistic assumption for any real…

cs.AI2023★ 102 cited

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani +2

The rapid advancement of chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conver…

cs.LG2023★ 2 cited

Computationally Budgeted Continual Learning: What Does Matter?

Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet Dokania +4

Continual Learning (CL) aims to sequentially train models on streams of incoming data that vary in distribution by preserving previous knowledge while adapting to new data. Current…