Collections
Discover the best community collections!
Collections including paper arxiv:2402.15000
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Evaluating Very Long-Term Conversational Memory of LLM Agents
Paper • 2402.17753 • Published • 18 -
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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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 49 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 136 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 18
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Divide-or-Conquer? Which Part Should You Distill Your LLM?
Paper • 2402.15000 • Published • 22 -
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU
Paper • 2403.06504 • Published • 53 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 75 -
AnyV2V: A Plug-and-Play Framework For Any Video-to-Video Editing Tasks
Paper • 2403.14468 • Published • 22
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Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 16 -
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation
Paper • 2401.15688 • Published • 11 -
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 69 -
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities
Paper • 2401.15071 • Published • 35
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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