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ReAct: Synergizing Reasoning and Acting in Language Models
Paper • 2210.03629 • Published • 12 -
Attention Is All You Need
Paper • 1706.03762 • Published • 35 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 11 -
Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 99
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Collections including paper arxiv:1810.04805
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Attention Is All You Need
Paper • 1706.03762 • Published • 35 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 11 -
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 6 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 10
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Attention Is All You Need
Paper • 1706.03762 • Published • 35 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 11 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 11 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 10
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Distributed Representations of Sentences and Documents
Paper • 1405.4053 • Published -
Sequence to Sequence Learning with Neural Networks
Paper • 1409.3215 • Published • 3 -
PaLM: Scaling Language Modeling with Pathways
Paper • 2204.02311 • Published • 1 -
Recent Trends in Deep Learning Based Natural Language Processing
Paper • 1708.02709 • Published
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 11 -
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Paper • 1907.11692 • Published • 7 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 10 -
OPT: Open Pre-trained Transformer Language Models
Paper • 2205.01068 • Published • 1
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Attention Is All You Need
Paper • 1706.03762 • Published • 35 -
Self-Attention with Relative Position Representations
Paper • 1803.02155 • Published -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 11 -
Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding
Paper • 2401.12954 • Published • 28
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 11 -
Transformers Can Achieve Length Generalization But Not Robustly
Paper • 2402.09371 • Published • 12 -
Triple-Encoders: Representations That Fire Together, Wire Together
Paper • 2402.12332 • Published • 2
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Lost in the Middle: How Language Models Use Long Contexts
Paper • 2307.03172 • Published • 31 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 11 -
Attention Is All You Need
Paper • 1706.03762 • Published • 35 -
Llama 2: Open Foundation and Fine-Tuned Chat Models
Paper • 2307.09288 • Published • 235
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Nemotron-4 15B Technical Report
Paper • 2402.16819 • Published • 40 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 50 -
RWKV: Reinventing RNNs for the Transformer Era
Paper • 2305.13048 • Published • 10 -
Reformer: The Efficient Transformer
Paper • 2001.04451 • Published