Scaling Instruction-Finetuned Language Models
Paper
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2210.11416
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Published
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7
Papers
Papers I find interesting
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Common 7B Language Models Already Possess Strong Math Capabilities
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Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters
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StarCoder 2 and The Stack v2: The Next Generation
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Simple linear attention language models balance the recall-throughput tradeoff
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When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
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Nemotron-4 15B Technical Report
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FuseChat: Knowledge Fusion of Chat Models
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MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
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StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
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Do Large Language Models Latently Perform Multi-Hop Reasoning?
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Watermarking Makes Language Models Radioactive
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GPTVQ: The Blessing of Dimensionality for LLM Quantization
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Gemma: Open Models Based on Gemini Research and Technology
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MoAI: Mixture of All Intelligence for Large Language and Vision Models
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Simple and Scalable Strategies to Continually Pre-train Large Language Models
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Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
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MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
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PERL: Parameter Efficient Reinforcement Learning from Human Feedback
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Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
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