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Sep 9, 2023
Sep 9, 2023
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Collections including paper arxiv:2309.03409
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Dec 20, 2023
Dec 20, 2023
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Large Language Models as Optimizers
Paper • 2309.03409 • Published • 72 -
One Wide Feedforward is All You Need
Paper • 2309.01826 • Published • 31 -
Self-Alignment with Instruction Backtranslation
Paper • 2308.06259 • Published • 38 -
Shepherd: A Critic for Language Model Generation
Paper • 2308.04592 • Published • 27
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Sep 9, 2023
Sep 9, 2023
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Apr 12
Apr 12
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Oct 16, 2023
Oct 16, 2023
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Robotic Table Tennis: A Case Study into a High Speed Learning System
Paper • 2309.03315 • Published • 5 -
FLM-101B: An Open LLM and How to Train It with $100K Budget
Paper • 2309.03852 • Published • 42 -
GPT Can Solve Mathematical Problems Without a Calculator
Paper • 2309.03241 • Published • 17 -
Large Language Models as Optimizers
Paper • 2309.03409 • Published • 72
Collection by
Apr 15
Apr 15
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Large Language Models as Optimizers
Paper • 2309.03409 • Published • 72 -
Challenges and Applications of Large Language Models
Paper • 2307.10169 • Published • 46 -
Efficiently Modeling Long Sequences with Structured State Spaces
Paper • 2111.00396 • Published • 1 -
DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning
Paper • 2006.08381 • Published
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Sep 8, 2023
Sep 8, 2023
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Sep 8, 2023
Sep 8, 2023
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Mar 21
Mar 21
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DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Paper • 2309.03883 • Published • 14 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 25 -
Agents: An Open-source Framework for Autonomous Language Agents
Paper • 2309.07870 • Published • 39 -
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Paper • 2309.00267 • Published • 45
Collection by
Sep 20, 2023
Sep 20, 2023
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Large Language Models as Optimizers
Paper • 2309.03409 • Published • 72 -
When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale
Paper • 2309.04564 • Published • 14 -
LIMA: Less Is More for Alignment
Paper • 2305.11206 • Published • 19 -
Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents
Paper • 2302.01560 • Published