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DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search
Paper • 2408.08152 • Published • 60 -
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition
Paper • 2402.15220 • Published • 21 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 56 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 20
Collections
Discover the best community collections!
Collections including paper arxiv:2404.08634
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YAYI 2: Multilingual Open-Source Large Language Models
Paper • 2312.14862 • Published • 15 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 60 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69 -
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Paper • 2401.06066 • Published • 58
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The Generative AI Paradox: "What It Can Create, It May Not Understand"
Paper • 2311.00059 • Published • 20 -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 50 -
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
Paper • 2403.07816 • Published • 44 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 59
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Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads
Paper • 2401.10774 • Published • 59 -
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding
Paper • 2401.06761 • Published • 1 -
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache
Paper • 2401.02669 • Published • 16 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 60
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ChatAnything: Facetime Chat with LLM-Enhanced Personas
Paper • 2311.06772 • Published • 35 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 30 -
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Instruction-Following Evaluation for Large Language Models
Paper • 2311.07911 • Published • 22
-
DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search
Paper • 2408.08152 • Published • 60 -
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition
Paper • 2402.15220 • Published • 21 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 56 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 20
-
Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads
Paper • 2401.10774 • Published • 59 -
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding
Paper • 2401.06761 • Published • 1 -
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache
Paper • 2401.02669 • Published • 16 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 60
-
YAYI 2: Multilingual Open-Source Large Language Models
Paper • 2312.14862 • Published • 15 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 60 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 69 -
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Paper • 2401.06066 • Published • 58
-
ChatAnything: Facetime Chat with LLM-Enhanced Personas
Paper • 2311.06772 • Published • 35 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 30 -
Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
Paper • 2311.07989 • Published • 26 -
Instruction-Following Evaluation for Large Language Models
Paper • 2311.07911 • Published • 22
-
The Generative AI Paradox: "What It Can Create, It May Not Understand"
Paper • 2311.00059 • Published • 20 -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 50 -
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
Paper • 2403.07816 • Published • 44 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 59