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Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Paper • 2309.08532 • Published • 52 -
Multimodal Foundation Models: From Specialists to General-Purpose Assistants
Paper • 2309.10020 • Published • 40 -
SlimPajama-DC: Understanding Data Combinations for LLM Training
Paper • 2309.10818 • Published • 10
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Collections including paper arxiv:2309.10020
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Stabilizing RLHF through Advantage Model and Selective Rehearsal
Paper • 2309.10202 • Published • 9 -
Multimodal Foundation Models: From Specialists to General-Purpose Assistants
Paper • 2309.10020 • Published • 40 -
OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
Paper • 2402.14658 • Published • 82
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Self-Alignment with Instruction Backtranslation
Paper • 2308.06259 • Published • 41 -
ReCLIP: Refine Contrastive Language Image Pre-Training with Source Free Domain Adaptation
Paper • 2308.03793 • Published • 10 -
From Sparse to Soft Mixtures of Experts
Paper • 2308.00951 • Published • 20 -
Revisiting DETR Pre-training for Object Detection
Paper • 2308.01300 • Published • 9
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MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
Paper • 2309.04662 • Published • 22 -
Neurons in Large Language Models: Dead, N-gram, Positional
Paper • 2309.04827 • Published • 16 -
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Paper • 2309.05516 • Published • 9 -
DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs
Paper • 2309.03907 • Published • 8
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Large Language Models as Optimizers
Paper • 2309.03409 • Published • 75 -
FLM-101B: An Open LLM and How to Train It with $100K Budget
Paper • 2309.03852 • Published • 43 -
GPT Can Solve Mathematical Problems Without a Calculator
Paper • 2309.03241 • Published • 17 -
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Paper • 2309.03883 • Published • 33