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When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 23 -
Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Paper • 2402.14848 • Published • 18 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 25 -
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model
Paper • 2402.07827 • Published • 43
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Collections including paper arxiv:2402.14848
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Evaluating Very Long-Term Conversational Memory of LLM Agents
Paper • 2402.17753 • Published • 17 -
StructLM: Towards Building Generalist Models for Structured Knowledge Grounding
Paper • 2402.16671 • Published • 26 -
Do Large Language Models Latently Perform Multi-Hop Reasoning?
Paper • 2402.16837 • Published • 24 -
Divide-or-Conquer? Which Part Should You Distill Your LLM?
Paper • 2402.15000 • Published • 22
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Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Paper • 2402.14848 • Published • 18 -
Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 43 -
How Far Are We from Intelligent Visual Deductive Reasoning?
Paper • 2403.04732 • Published • 18 -
Learning to Reason and Memorize with Self-Notes
Paper • 2305.00833 • Published • 4
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InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory
Paper • 2402.04617 • Published • 4 -
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences
Paper • 2403.09347 • Published • 20 -
Resonance RoPE: Improving Context Length Generalization of Large Language Models
Paper • 2403.00071 • Published • 19 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 17