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Learning Transferable Visual Models From Natural Language Supervision
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Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
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Training Language Models to Follow Instructions with Human Feedback (InstructGPT)
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Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
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Improving Factuality and Reasoning in Language Models through Multiagent Debate
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Self-Rewarding Language Models
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REALM: Retrieval-Augmented Language Model Pre-Training
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Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
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Prefix-Tuning: Optimizing Continuous Prompts for Generation
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Improving Language Understanding by Generative Pre-Training
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Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate
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Gamma Poisson Shrinker
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Simplifying Transformer Blocks
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Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement
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Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves
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Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
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Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks
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Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
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Large Language Models are Zero-Shot Reasoners
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
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ALBERT: A Lite BERT for Self-Supervised Learning of Languange Representations
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DistilBERT, a distilled version of BERT: smaller, faster and lighter
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DeBERTa: Decoding-Enhanced BERT with Disentangled Attention
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RoBERTa: A Robustly Optimized BERT Pretraining Approach
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BERT: Bidirectional Encoder Representations from Transformers
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Navie Bayes