Editing CXCSCMU GroupWiki (section)

=== Meeting 1 - October 6, 2023 ===
{| class="wikitable"
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!Paper
!#Votes
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|[https://openreview.net/pdf?id=WgbcOQMNXB Large Language Models Are Not Zero-Shot Communicators]
|2
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|[https://openreview.net/pdf?id=c4m0BkO4OL Towards Structured Sparsity in Transformers for Efficient Inference]
|3
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|[https://arxiv.org/pdf/2305.02869.pdf 2x Faster Language Model Pre-training via Masked Structural Growth]
|1
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|[https://arxiv.org/pdf/2309.17453.pdf Efficient Streaming Language Models with Attention Sinks]
|1
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|[https://arxiv.org/abs/2308.07922 RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models]
|0
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|[https://arxiv.org/pdf/2309.11495.pdf Chain-of-Verification Reduces Hallucination in Large Language Models]
|3
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|[https://arxiv.org/abs/2304.13060 Pre-train on just structure: Understanding linguistic inductive biases using transfer learning]
|2
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|[https://arxiv.org/pdf/2302.06675.pdf Symbolic Discovery of Optimization Algorithms] 
|0
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|[https://arxiv.org/pdf/2204.00185.pdf Distill-VQ: Learning Retrieval Oriented Vector Quantization By Distilling Knowledge from Dense Embeddings]
|3
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|[https://arxiv.org/abs/2206.02743 A Neural Corpus Indexer for Document Retrieval]
|1
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|[https://arxiv.org/pdf/2309.15088.pdf RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models]
|1
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|[https://arxiv.org/pdf/2309.07124.pdf RAIN: Your Language Models Can Align Themselves without Finetuning]
|0
|}