Collections
Discover the best community collections!
Collections including paper arxiv:2405.09220
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Iterative Reasoning Preference Optimization
Paper • 2404.19733 • Published • 47 -
Better & Faster Large Language Models via Multi-token Prediction
Paper • 2404.19737 • Published • 73 -
ORPO: Monolithic Preference Optimization without Reference Model
Paper • 2403.07691 • Published • 62 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 108
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AtP*: An efficient and scalable method for localizing LLM behaviour to components
Paper • 2403.00745 • Published • 11 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602 -
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT
Paper • 2402.16840 • Published • 23 -
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 111
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LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 6 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 16 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 10 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 65
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Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Paper • 2402.14083 • Published • 47 -
Linear Transformers are Versatile In-Context Learners
Paper • 2402.14180 • Published • 6 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 19 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 602
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 99 -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 46 -
PERL: Parameter Efficient Reinforcement Learning from Human Feedback
Paper • 2403.10704 • Published • 57 -
MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Paper • 2403.02884 • Published • 15
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 16 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 28 -
The Impact of Reasoning Step Length on Large Language Models
Paper • 2401.04925 • Published • 16