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Collections including paper arxiv:2402.04494

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 21
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 31
The Impact of Reasoning Step Length on Large Language Models

Paper • 2401.04925 • Published Jan 10, 2024 • 18

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Perception and abstraction. Each modality is tokenized and embedded into vectors for model to comprehend.

VILA^2: VILA Augmented VILA

Paper • 2407.17453 • Published Jul 24, 2024 • 41
Octopus v4: Graph of language models

Paper • 2404.19296 • Published Apr 30, 2024 • 118
Octo-planner: On-device Language Model for Planner-Action Agents

Paper • 2406.18082 • Published Jun 26, 2024 • 48
Dolphin: Long Context as a New Modality for Energy-Efficient On-Device Language Models

Paper • 2408.15518 • Published Aug 28, 2024 • 42

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 628

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 23
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30, 2024 • 21
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17, 2024 • 31
The Impact of Reasoning Step Length on Large Language Models

Paper • 2401.04925 • Published Jan 10, 2024 • 18

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Perception and abstraction. Each modality is tokenized and embedded into vectors for model to comprehend.

VILA^2: VILA Augmented VILA

Paper • 2407.17453 • Published Jul 24, 2024 • 41
Octopus v4: Graph of language models

Paper • 2404.19296 • Published Apr 30, 2024 • 118
Octo-planner: On-device Language Model for Planner-Action Agents

Paper • 2406.18082 • Published Jun 26, 2024 • 48
Dolphin: Long Context as a New Modality for Energy-Efficient On-Device Language Models

Paper • 2408.15518 • Published Aug 28, 2024 • 42

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 628

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

Grandmaster-Level Chess Without Search

Paper • 2402.04494 • Published Feb 7, 2024 • 69

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