Editing CXCSCMU GroupWiki (section)

=== Meeting 3 - December 1, 2023 ===
{| class="wikitable"
!Paper
!#Votes
|-
|[https://arxiv.org/abs/2112.08633 Learning To Retrieve Prompts for In-Context Learning]
|3
|-
|[https://arxiv.org/pdf/2311.03099.pdf Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch]
|2
|-
|[https://arxiv.org/abs/2310.10638 In-Context Pretraining: Language Modeling Beyond Document Boundaries]
|2
|-
|[https://arxiv.org/pdf/2311.11829.pdf System 2 Attention]
|2
|-
|[https://arxiv.org/pdf/2311.15436.pdf Learning to Skip for Language Modeling]
|2
|-
|[https://arxiv.org/pdf/2306.17842.pdf SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs]
|2
|-
|[https://openaccess.thecvf.com/content/ICCV2023/papers/Jin_Growing_a_Brain_with_Sparsity-Inducing_Generation_for_Continual_Learning_ICCV_2023_paper.pdf Growing a Brain with Sparsity-Inducing Generation for Continual Learning]
|2
|-
|[https://arxiv.org/abs/1911.00172 Generalization through Memorization: Nearest Neighbor Language Models]
|2
|-
|[https://arxiv.org/pdf/2309.08872.pdf PDFTriage: Question Answering over Long, Structured Documents]
|1
|-
|[https://arxiv.org/pdf/2311.01906.pdf Simplifying Transformer Blocks]
|1
|-
|[https://arxiv.org/abs/2311.03348 Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models]
|1
|-
|[https://arxiv.org/pdf/2311.05965v1.pdf Large Language Models are Zero Shot Hypothesis Proposers]
|0
|-
|[https://arxiv.org/pdf/2303.17605.pdf SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer]
|0
|-
|[https://arxiv.org/abs/2310.07298 Beyond Memorization: Violating Privacy Via Inference with Large Language Models]
|0
|}