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Collections including paper arxiv:2404.03592

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Paper • 2404.12253 • Published Apr 18, 2024 • 55
Make Your LLM Fully Utilize the Context

Paper • 2404.16811 • Published Apr 25, 2024 • 55
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11, 2024 • 93
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Paper • 2404.10667 • Published Apr 16, 2024 • 22
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20, 2024 • 26
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14, 2024 • 29

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

papers-efficiency

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

Paper • 2404.02258 • Published Apr 2, 2024 • 107
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

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, 2024 • 101

Extending Llama-3's Context Ten-Fold Overnight

Paper • 2404.19553 • Published Apr 30, 2024 • 34
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101
Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck

Paper • 2404.07647 • Published Apr 11, 2024 • 4
SciGLM: Training Scientific Language Models with Self-Reflective Instruction Annotation and Tuning

Paper • 2401.07950 • Published Jan 15, 2024 • 4

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

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

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

The Unreasonable Ineffectiveness of the Deeper Layers

Paper • 2403.17887 • Published Mar 26, 2024 • 82
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 107
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences

Paper • 2404.03715 • Published Apr 4, 2024 • 62

Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15, 2024 • 109
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Paper • 2404.12253 • Published Apr 18, 2024 • 55
Make Your LLM Fully Utilize the Context

Paper • 2404.16811 • Published Apr 25, 2024 • 55
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

Extending Llama-3's Context Ten-Fold Overnight

Paper • 2404.19553 • Published Apr 30, 2024 • 34
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101
Why do small language models underperform? Studying Language Model Saturation via the Softmax Bottleneck

Paper • 2404.07647 • Published Apr 11, 2024 • 4
SciGLM: Training Scientific Language Models with Self-Reflective Instruction Annotation and Tuning

Paper • 2401.07950 • Published Jan 15, 2024 • 4

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11, 2024 • 93
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Paper • 2404.10667 • Published Apr 16, 2024 • 22
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20, 2024 • 26
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14, 2024 • 29

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

papers-efficiency

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

Paper • 2404.02258 • Published Apr 2, 2024 • 107
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

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

ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101

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, 2024 • 101

The Unreasonable Ineffectiveness of the Deeper Layers

Paper • 2403.17887 • Published Mar 26, 2024 • 82
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2, 2024 • 107
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4, 2024 • 101
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences

Paper • 2404.03715 • Published Apr 4, 2024 • 62

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