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Collections including paper arxiv:2404.03592

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 143
Orion-14B: Open-source Multilingual Large Language Models

Paper • 2401.12246 • Published Jan 20 • 11
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 50
MM-LLMs: Recent Advances in MultiModal Large Language Models

Paper • 2401.13601 • Published Jan 24 • 44

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11 • 84
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Paper • 2404.10667 • Published Apr 16 • 17
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20 • 24
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14 • 26

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89

papers-efficiency

Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2 • 104
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89

Papers - Fine-tuning - Report - Llama 7B and 13B

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89

Papers - Fine-tuning - ReFT

In this paper, we propose a strong alternative to PEFTs, LoReFT. LoReFT achieves strong per- formance across benchmarks from four domains while being

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89

The Unreasonable Ineffectiveness of the Deeper Layers

Paper • 2403.17887 • Published Mar 26 • 78
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2 • 104
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences

Paper • 2404.03715 • Published Apr 4 • 60

Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28 • 104
sDPO: Don't Use Your Data All at Once

Paper • 2403.19270 • Published Mar 28 • 39
ViTAR: Vision Transformer with Any Resolution

Paper • 2403.18361 • Published Mar 27 • 52
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Paper • 2403.18814 • Published Mar 27 • 44

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